Laryngeal surface reconstructions from monocular endoscopic videos: a structure from motion pipeline for periodic deformations

PURPOSE

Surface reconstructions from laryngoscopic videos have the potential to assist clinicians in diagnosing, quantifying, and monitoring airway diseases using minimally invasive techniques. However, tissue movements and deformations make these reconstructions challenging using conventional pipelines.

METHODS

To facilitate such reconstructions, we developed video frame pre-filtering and featureless dense matching steps to enhance the Alicevision Meshroom SfM pipeline. Time and the anterior glottic angle were used to approximate the rigid state of the airway and to collect frames with different camera poses. Featureless dense matches were tracked with a correspondence transformer across subsets of images to extract matched points that could be used to estimate the point cloud and reconstructed surface. The proposed pipeline was tested on a simulated dataset under various conditions like illumination and resolution as well as real laryngoscopic videos.

RESULTS

Our pipeline was able to reconstruct the laryngeal region based on 4, 8, and 16 images obtained from simulated and real patient exams. The pipeline was robust to sparse inputs, blur, and extreme lighting conditions, unlike the Meshroom pipeline which failed to produce a point cloud for 6 of 15 simulated datasets.

CONCLUSION

The pre-filtering and featureless dense matching modules specialize the conventional SfM pipeline to handle the challenging laryngoscopic examinations, directly from patient videos. These 3D visualizations have the potential to improve spatial understanding of airway conditions.

Dataset on unmanned aerial vehicle multispectral images acquired over a vineyard affected by Botrytis cinerea in northern Spain

Remote sensing makes it possible to gather data rapidly, precisely, accurately, and non-destructively, allowing it to assess grapevines accurately in near real-time. In addition, multispectral cameras capture information in different bands, which can be combined to generate vegetation indices useful in precision agriculture. This dataset contains 16,504 multispectral images from a 1.06 ha vineyard affected by Botrytis cinerea, in the north of Spain. The photos were taken throughout four UAV flights at 30 m height with varying camera angles on 16 September 2021, the same date as the grape harvest. The first flight took place with the camera tilted at 0° (nadir angle), the second flight at 30°, the third flight at 45°, and the fourth flight was also performed at 0° but was scheduled in the afternoon to capture the shadows of the plants projected on the ground. This dataset was created to support researchers interested in disease detection and, in general, UAV remote sensing in vineyards and other woody crops. Moreover, it allows digital photogrammetry and 3D reconstruction in the context of precision agriculture, enabling the study of the effect of different tilt angles on the 3D reconstruction of the vineyard and the generation of orthomosaics.

Estimation of cotton canopy parameters based on unmanned aerial vehicle (UAV) oblique photography

BACKGROUND

The technology of cotton defoliation is essential for mechanical cotton harvesting. Agricultural unmanned aerial vehicle (UAV) spraying has the advantages of low cost, high efficiency and no mechanical damage to cotton and has been favored and widely used by cotton planters in China. However, there are also some problems of low cotton defoliation rates and high impurity rates caused by unclear spraying amounts of cotton defoliants. The chemical rate recommendation and application should be based upon crop canopy volume rather than on land area. Plant height and leaf area index (LAI) is directly connected to plant canopy structure. Accurate dynamic monitoring of plant height and LAI provides important information for evaluating cotton growth and production. The traditional method to obtain plant height and LAI was s a time-consuming and labor-intensive task. It is very difficult and unrealistic to use the traditional measurement method to make the temporal and spatial variation map of plant height and LAI of large cotton fields. With the application of UAV in agriculture, remote sensing by UAV is currently regarded as an effective technology for monitoring and estimating plant height and LAI.

RESULTS

In this paper, we used UAV RGB photos to build dense point clouds to estimate cotton plant height and LAI following cotton defoliant spraying. The results indicate that the proposed method was able to dynamically monitor the changes in the LAI of cotton at different times. At 3 days after defoliant spraying, the correlation between the plant height estimated based on the constructed dense point cloud and the measured plant height was strong, with [Formula: see text] and RMSE values of 0.962 and 0.913, respectively. At 10 days after defoliant spraying, the correlation became weaker over time, with [Formula: see text] and RMSE values of 0.018 and 0.027, respectively. Comparing the actual manually measured LAI with the estimated LAI based on the dense point cloud, the [Formula: see text] and RMSE were 0.872 and 0.814 and 0.132 and 0.173 at 3 and 10 days after defoliant spraying, respectively.

CONCLUSIONS

Dense point cloud construction based on UAV remote sensing is a potential alternative to plant height and LAI estimation. The accuracy of LAI estimation can be improved by considering both plant height and planting density.

Probabilistic hydro-geomorphological hazard assessment based on UAV-derived high-resolution topographic data: The case of Basento river (Southern Italy)

The combined use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) photogrammetry allows the collection and processing of high-resolution data on demand, which is key for the constant and detailed monitoring of the fluvial environment. In addition, through the ever-increasing development of new techniques of mapping and data processing (i.e., UAVs swarm, BVLOS flight missions, high-performance photogrammetry workflow), it is now possible to detect large areas at high-resolution, providing support for spatiotemporal insights into hydro-geomorphological processes and hazard assessment, in order to ensure an effective management and to prevent catastrophic phenomena (i.e., floods). The main goal of this paper is to use UAV-based high-resolution topographic data to constrain the probabilistic hazard assessment of extended reaches of Basento river (Basilicata, Italy). To demonstrate the influence of geomorphology and riverbed sediment on hazard assessment, a sensitivity analysis was carried out on the resolution of the UAV-derived DEMs; on the riverbed roughness coefficient resulting from photo-sieving analysis and on the morphological change detection over short-time ranges (2019-2021). We found that lower resolution DEMs lead to an increase of flooding probability (in several river cross-sections an increase even higher than 99 % resulted), and that a greater roughness coefficient involves an increase in the probability of flooding (with a maximum increase of about 9 %). Moreover, the multitemporal high-resolution outputs resulting from SfM allowed the identification of morphological changes, in short-times, caused by an anthropic modification of the river bank, which significantly affected the flooding hazard.

Coral micro-fragmentation assays for optimizing active reef restoration efforts

The global decline of coral reefs has driven considerable interest in active coral restoration. Despite their importance and dominance on mature reefs, relatively few coral restoration projects use slower growth forms like massive and encrusting coral species. Micro-fragmentation can increase coral cover by orders of magnitude faster than natural growth, which now allows cultivation of slow growing massive forms and shows promise and flexibility for active reef restoration. However, the major causes of variation in growth and survival of outplanted colonies remain poorly understood. Here, we report simple outplanting assays to aid in active reef restoration of slower growing species and increase the likelihood of restoration success. We used two different micro-fragmentation assays. Pyramid assays were used to examine variation associated with fragment size (ranging from ≈1-9 cm²), nursery residence time (for both in-situ and ex-situ nurseries), and 2D vs. 3D measurements of growth. Block assays were used to examine spatial variation among individual performance at outplanting sites in the field. We found 2D and 3D measurements correlated well, so measured survivorship and growth using top-down planar images for two of the main Hawaiian reef building corals, the plating Montipora capitata and the massive Porites compressa. Pyramid assays housed and outplanted from the in-situ nursery showed no effect of residence time or size on overall survivorship or growth for either species. Results from the ex-situ nursery, however, varied by species, with P. compressa again showing no effect of nursery residence time or size on survivorship or growth. In contrast, nursery culture resulted in improved survivorship of small M. capitata fragments, but net growth showed a weak positive effect of nursery time for medium fragments. Small fragments still suffered higher mortality than either medium or large fragments. Due to their lower mortality, medium fragments (≈3 cm²) appear to be the best compromise between growth and survivorship for outplanting. Likewise, given weak positive gains relative to the investment, our results suggest that it could be more cost-effective to simply outplant medium fragments as soon as possible, without intermediate culture in a nursery. Furthermore, the block assay revealed significant differences in survivorship and growth among sites for individuals of both species, emphasizing the importance of considering spatial variation in coral survival and growth following outplanting. These results highlight the value of using short-term micro-fragmentation assays prior to outplanting to assess size, and location specific performance, optimizing the efficiency of active reef restoration activities and maximizing the probability of success for active coral restoration projects.

Understory biomass measurement in a dense plantation forest based on drone-SfM data by a manual low-flying drone under the canopy

Forest is an important part of the environmental system, which has a significant impact on soil hydrological characteristics and forest landscapes, because these processes are influenced by forest management and understory vegetation. Quantitative understory vegetation biomass (UVB) measurement and estimation are vital processes in forest ecology and environmental management. However, these estimations are difficult to make on a large scale especially dense planted forest. Here, we applied catchment-scale Structure from Motion and a manually operated ultralow-flying drone under the canopy of a dense planted (2000 stems/ha) Japanese cedar/cypress plantation forest to reconstruct the understory. An understory drone survey was performed over a 1.1-ha sub-catchment to generate a canopy height model based on dense point cloud data. A biomass survey of three 16-m² harvesting plots was conducted to compute understory vegetation volume data based on point clouds. Combined with harvested biomass data in the field, quantitative models were developed between the understory vegetation volume and biomass. Subsequently, the models were used to map spatial understory vegetation biomass distribution in the sub-catchments. Aerial photos taken by the ultralow-flying drones under the canopy yielded a high-resolution catchment-scale understory with point cloud density >10/cm². Strong cubic model coefficients of determination (R² = 0.75) predicted the understory vegetation biomass based on the canopy height model. The mean understory vegetation biomass was 0.82 kg/m² and dominated by low ferns. In the present study, we successfully reconstructed the multilayered forest structure and generated understory vegetation biomass distribution models. This results also will be essential to evaluate the erosion and evapotranspiration in dense plantation forests and future environmental management.

Reduced 2D form coherence and 3D structure from motion sensitivity in developmental dyscalculia

Developmental dyscalculia (DD) is a specific learning disability affecting the development of numerical and arithmetical skills. The origin of DD is typically attributed to the suboptimal functioning of key regions within the dorsal visual stream (parietal cortex) which support numerical cognition. While DD individuals are often impaired in visual numerosity perception, the extent to which they also show a wider range of visual dysfunctions is poorly documented. In the current study we measured sensitivity to global motion (translational and flow), 2D static form (Glass patterns) and 3D structure from motion in adults with DD and control subjects. While sensitivity to global motion was comparable across groups, thresholds for static form and structure from motion were higher in the DD compared to the control group, irrespective of associated reading impairments. Glass pattern sensitivity predicted numerical abilities, and this relation could not be explained by recently reported differences in visual crowding. Since global form sensitivity has often been considered an index of ventral stream function, our findings could indicate a cortical dysfunction extending beyond the dorsal visual stream. Alternatively, they would fit with a role of parietal cortex in form perception under challenging conditions requiring multiple element integration.

Using 3D photogrammetry to quantify the subtle differences of coral reefs under the impacts of marine activities

Marine activities may cause the degradation of coral reefs. The composition of benthic communities and seawater quality have been commonly used as the proxies to assess the impacts of marine activities. However, these proxies may not be able to detect the subtle differences within homogeneous environment. We used photogrammetry to quantify the subtle differences of structural complexity between heavily and lightly trafficked sites at Wanlitong, southern Taiwan. Our study demonstrated that the impacts of marine activities can be detected within tens of meters through quantifying structural complexity of coral reefs. Vector ruggedness measure (VRM) is a more suitable metric than conventional linear rugosity to detect such impacts. The correlations between structural complexity and coral cover have variances while comparing with previous studies. The results show that using photogrammetry to quantify the structure of coral reefs can provide a novel aspect to evaluate the subtle differences caused by marine activities.

Controlled photogrammetry system for determination of volume and surface features in soils

Quantitative and qualitative determination of total volume and surface features of a soil specimen is important in geotechnical engineering. Available methods suffer from a variety of shortcomings such as sample disturbance, equipment calibration, and lack of precision. The Controlled Photogrammetry System (CPS) is based on Structure-from-Motion (SfM) to capture a series of photographs and transform the images into a referenced three-dimensional model.

• This paper develops the Controlled Photogrammetry System.

• This paper describes the design and operation of the Controlled Photogrammetry System.

• This paper presents data processing and test results for a sand and clay.

Dynamic dot displays reveal material motion network in the human brain

There is growing research interest in the neural mechanisms underlying the recognition of material categories and properties. This research field, however, is relatively more recent and limited compared to investigations of the neural mechanisms underlying object and scene category recognition. Motion is particularly important for the perception of non-rigid materials, but the neural basis of non-rigid material motion remains unexplored. Using fMRI, we investigated which brain regions respond preferentially to material motion versus other types of motion. We introduce a new database of stimuli - dynamic dot materials - that are animations of moving dots that induce vivid percepts of various materials in motion, e.g. flapping cloth, liquid waves, wobbling jelly. Control stimuli were scrambled versions of these same animations and rigid three-dimensional rotating dots. Results showed that isolating material motion properties with dynamic dots (in contrast with other kinds of motion) activates a network of cortical regions in both ventral and dorsal visual pathways, including areas normally associated with the processing of surface properties and shape, and extending to somatosensory and premotor cortices. We suggest that such a widespread preference for material motion is due to strong associations between stimulus properties. For example viewing dots moving in a specific pattern not only elicits percepts of material motion; one perceives a flexible, non-rigid shape, identifies the object as a cloth flapping in the wind, infers the object's weight under gravity, and anticipates how it would feel to reach out and touch the material. These results are a first important step in mapping out the cortical architecture and dynamics in material-related motion processing.

Successful application of a novel technique to quantify negative impacts of derelict fishing nets on Northwestern Hawaiian Island reefs

The remote and uninhabited Northwestern Hawaiian Islands (NWHI) contain 70% of the shallow water coral reefs in the United States and are regularly exposed to derelict fishing nets. These nets snag on the shallow reefs, damaging or killing benthic communities. However, no data exist to quantify this impact. Here we use a novel application of photogrammetry, Structure-from-Motion (SfM), to calculate benthic cover from mosaic images at net-impact and control sites. Net-impact sites had significantly higher cover of bare substrate, sand, and crustose coralline algae and significantly lower coral and macroalgae cover compared to control sites. These differences were unrelated to net size and fouling. Our study demonstrates the utility of using SfM to efficiently quantify impacts of derelict fishing nets. Revisiting these sites will be essential to document how the reef recovers to further our understanding of the lasting impacts of derelict fishing nets on coral reef habitats.

High-resolution, non-invasive animal tracking and reconstruction of local environment in aquatic ecosystems

BACKGROUND

Acquiring high resolution quantitative behavioural data underwater often involves installation of costly infrastructure, or capture and manipulation of animals. Aquatic movement ecology can therefore be limited in taxonomic range and ecological coverage.

METHODS

Here we present a novel deep-learning based, multi-individual tracking approach, which incorporates Structure-from-Motion in order to determine the 3D location, body position and the visual environment of every recorded individual. The application is based on low-cost cameras and does not require the animals to be confined, manipulated, or handled in any way.

RESULTS

Using this approach, single individuals, small heterospecific groups and schools of fish were tracked in freshwater and marine environments of varying complexity. Positional tracking errors as low as 1.09 ± 0.47 cm (RSME) in underwater areas up to 500 m2 were recorded.

CONCLUSIONS

This cost-effective and open-source framework allows the analysis of animal behaviour in aquatic systems at an unprecedented resolution. Implementing this versatile approach, quantitative behavioural analysis can be employed in a wide range of natural contexts, vastly expanding our potential for examining non-model systems and species.

Wound area measurement with 3D transformation and smartphone images

BACKGROUND

Quantitative areas is of great measurement of wound significance in clinical trials, wound pathological analysis, and daily patient care. 2D methods cannot solve the problems caused by human body curvatures and different camera shooting angles. Our objective is to simply collect wound areas, accurately measure wound areas and overcome the shortcomings of 2D methods.

RESULTS

We propose a method with 3D transformation to measure wound area on a human body surface, which combines structure from motion (SFM), least squares conformal mapping (LSCM), and image segmentation. The method captures 2D images of wound, which is surrounded by adhesive tape scale next to it, by smartphone and implements 3D reconstruction from the images based on SFM. Then it uses LSCM to unwrap the UV map of the 3D model. In the end, it utilizes image segmentation by interactive method for wound extraction and measurement. Our system yields state-of-the-art results on a dataset of 118 wounds on 54 patients, and performs with an accuracy of 0.97. The Pearson correlation, standardized regression coefficient and adjusted R square of our method are 0.999, 0.895 and 0.998 respectively.

CONCLUSIONS

A smartphone is used to capture wound images, which lowers costs, lessens dependence on hardware, and avoids the risk of infection. The quantitative calculation of the 3D wound area is realized, solving the challenges that 2D methods cannot and achieving a good accuracy.

Symmetry mediates the bootstrapping of 3-D relief slant to metric slant

Empirical studies have always shown 3-D slant and shape perception to be inaccurate as a result of relief scaling (an unknown scaling along the depth direction). Wang, Lind, and Bingham (Journal of Experimental Psychology: Human Perception and Performance, 44(10), 1508-1522, 2018) discovered that sufficient relative motion between the observer and 3-D objects in the form of continuous perspective change (≥45°) could enable accurate 3-D slant perception. They attributed this to a bootstrap process (Lind, Lee, Mazanowski, Kountouriotis, & Bingham in Journal of Experimental Psychology: Human Perception and Performance, 40(1), 83, 2014) where the perceiver identifies right angles formed by texture elements and tracks them in the 3-D relief structure through rotation to extrapolate the unknown scaling factor, then used to convert 3-D relief structure to 3-D Euclidean structure. This study examined the nature of the bootstrap process in slant perception. In a series of four experiments, we demonstrated that (1) features of 3-D relief structure, instead of 2-D texture elements, were tracked (Experiment 1); (2) identifying right angles was not necessary, and a different implementation of the bootstrap process is more suitable for 3-D slant perception (Experiment 2); and (3) mirror symmetry is necessary to produce accurate slant estimation using the bootstrapped scaling factor (Experiments 3 and 4). Together, the results support the hypothesis that a symmetry axis is used to determine the direction of slant and that 3-D relief structure is tracked over sufficiently large perspective change to produce metric depth. Altogether, the results supported the bootstrap process.

Drone-based Structure-from-Motion provides accurate forest canopy data to assess shading effects in river temperature models

Climatic warming will increase river temperature globally, with consequences for cold water-adapted organisms. In regions with low forest cover, elevated river temperature is often associated with a lack of bankside shading. Consequently, river managers have advocated riparian tree planting as a strategy to reduce temperature extremes. However, the effect of riparian shading on river temperature varies substantially between locations. Process-based models can elucidate the relative importance of woodland and other factors driving river temperature and thus improve understanding of spatial variability of the effect of shading, but characterising the spatial distribution and height of riparian tree cover necessary to parameterise these models remains a significant challenge. Here, we document a novel approach that combines Structure-from-Motion (SfM) photogrammetry acquired from a drone to characterise the riparian canopy with a process based temperature model (Heat Source) to simulate the effects of tree shading on river temperature. Our approach was applied in the Girnock Burn, a tributary of the Aberdeenshire Dee, Scotland. Results show that SfM approximates true canopy elevation with a good degree of accuracy (R² = 0.96) and reveals notable spatial heterogeneity in shading. When these data were incorporated into a process-based temperature model, it was possible to simulate river temperatures with a similarly-high level of accuracy (RMSE <0.7 °C) to a model parameterised using 'conventional' LiDAR tree height data. We subsequently demonstrate the utility of our approach for quantifying the magnitude of shading effects on stream temperature by comparing simulated temperatures against another model from which all riparian woodland has been removed. Our findings highlight drone-based SfM as an effective tool for characterising riparian shading and improving river temperature models. This research provides valuable insights into the effects of riparian woodland on river temperature and the potential of bankside tree planting for climate change adaptation.

Estimating soil degradation in montane grasslands of North-eastern Italian Alps (Italy)

Grasslands cover a large portion of the terrestrial ecosystems, and are vital for biodiversity conservation, environmental protection and livestock husbandry. However, grasslands are degraded due to unreasonable management worldwide, i.e., soil erosion indirectly due to the damage of overgrazing on vegetation coverage and soil texture. An in-depth investigation is necessary to quantify soil erosion in alpine pastures, in order to manage grasslands more sustainably. In this work, we collected freely available satellite images and carried out intensive field surveys for the whole Autonomous Province of Trento (Northeastern Italian Alps) in 2016. The area (and volume) of soil erosions were then estimated and shown in maps. The average of the depths of soil erosion measured in field was used as a reference for estimating soil erosion of the entire study area. High-resolution DEMs difference in soil surface conditions was also computed in two representative areas between pre- and post-degradation to estimate the volume and the average depth of eroded soils. The degradation of soil in the study areas has been estimated in 144063 m² and an estimated volume of 33610 ± 1800 m³. Results indicate that our procedure can serve as a low-cost approach for a rapid estimation of soil erosion in mountain areas. Mapping soil erosion can improve the sustainability of grazing management system and reduce the risk of pastureland degradation at large spatial scales.

Intact perception of coherent motion, dynamic rigid form, and biological motion in chronic schizophrenia

BACKGROUND

Prior studies have documented biological motion perception deficits in schizophrenia, but it remains unclear whether the impairments arise from poor social cognition, perceptual organization, basic motion processing, or sustained attention/motivation. To address the issue, we had 24 chronic schizophrenia patients and 27 healthy controls perform three tasks: coherent motion, where subjects indicated whether a cloud of dots drifted leftward or rightward; dynamic rigid form, where subjects determined the tilt direction of a translating, point-light rectangle; and biological motion, where subjects judged whether a human point-light figure walked leftward or rightward. Task difficulty was staircase controlled and depended on the directional variability of the background dot motion. Catch trials were added to verify task attentiveness and engagement.

RESULTS

Patients and controls demonstrated similar performance thresholds and near-ceiling catch trial accuracy for each task (uncorrected ps > 0.1; ds < 0.35). In all but the coherent motion task, higher IQ correlated with better performance (ps < 0.001).

CONCLUSION

Schizophrenia patients have intact perception of motion coherence, dynamic rigid form, and biological motion at least for our sample and set-up. We speculate that previously documented biological motion perception deficits arose from task or stimulus differences or from group differences in IQ, attention, or motivation.

Photogrammetry using visible, infrared, hyperspectral and thermal imaging of crime scenes

Photogrammetry is a method for obtaining virtual 3D models of objects and scenes. The technique is increasingly used to record the crime scene in its original, undisturbed state for mapping, analytical and reconstruction purposes. Recently, it was shown that it is possible to visualize and/or chemically analyze latent traces by using advanced cameras which either operate in wavelength ranges beyond the visible range, and/or are able to obtain spectrally resolved images. The combination of these advanced cameras and photogrammetric techniques enables the 3D registration of valuable information. We successfully explored the feasibility to obtain visible, infrared, hyperspectral and thermal 3D registrations of simulated crime scenes using photogrammetry, and demonstrate the possibilities and practical challenges for use in forensic practice.

Out of sight, out of mind: Occlusion and eye closure destabilize moving bistable structure-from-motion displays

Our brain constantly tries to anticipate the future by using a variety of memory mechanisms. Interestingly, studies using the intermittent presentation of multistable displays have shown little perceptual persistence for interruptions longer than a few hundred milliseconds. Here we examined whether we can facilitate the perceptual stability of bistable displays following a period of invisibility by employing a physically plausible and ecologically valid occlusion event sequence, as opposed to the typical intermittent presentation, with sudden onsets and offsets. To this end, we presented a bistable rotating structure-from-motion display that was moving along a linear horizontal trajectory on the screen and either was temporarily occluded by another object (a cardboard strip in Exp. 1, a computer-generated image in Exp. 2) or became invisible due to eye closure (Exp. 3). We report that a bistable rotation direction reliably persisted following occlusion or interruption only (1) if the pre- and postinterruption locations overlapped spatially (an occluder with apertures in Exp. 2 or brief, spontaneous blinks in Exp. 3) or (2) if an object's size allowed for the efficient grouping of dots on both sides of the occluding object (large objects in Exp. 1). In contrast, we observed no persistence whenever the pre- and postinterruption locations were nonoverlapping (large solid occluding objects in Exps. 1 and 2 and long, prompted blinks in Exp. 3). We report that the bistable rotation direction of a moving object persisted only for spatially overlapping neural representations, and that persistence was not facilitated by a physically plausible and ecologically valid occlusion event.

A multi-scale approach of fluvial biogeomorphic dynamics using photogrammetry

Over the last twenty years, significant technical advances turned photogrammetry into a relevant tool for the integrated analysis of biogeomorphic cross-scale interactions within vegetated fluvial corridors, which will largely contribute to the development and improvement of self-sustainable river restoration efforts. Here, we propose a cost-effective, easily reproducible approach based on stereophotogrammetry and Structure from Motion (SfM) technique to study feedbacks between fluvial geomorphology and riparian vegetation at different nested spatiotemporal scales. We combined different photogrammetric methods and thus were able to investigate biogeomorphic feedbacks at all three spatial scales (i.e., corridor, alluvial bar and micro-site) and at three different temporal scales, i.e., present, recent past and long term evolution on a diversified riparian landscape mosaic. We evaluate the performance and the limits of photogrammetric methods by targeting a set of fundamental parameters necessary to study biogeomorphic feedbacks at each of the three nested spatial scales and, when possible, propose appropriate solutions. The RMSE varies between 0.01 and 2 m depending on spatial scale and photogrammetric methods. Despite some remaining difficulties to properly apply them with current technologies under all circumstances in fluvial biogeomorphic studies, e.g. the detection of vegetation density or landform topography under a dense vegetation canopy, we suggest that photogrammetry is a promising instrument for the quantification of biogeomorphic feedbacks at nested spatial scales within river systems and for developing appropriate river management tools and strategies.

The visual kinetic depth effect is altered with Parkinson's disease

BACKGROUND

People with Parkinson's disease (PD) often have visual-perceptual disorders. The goal of this study was to learn if they can develop a three dimensional (3D) percept that depends on the kinetic depth effect; that is, the viewer's ability to spatially integrate over time images that are moving along many trajectories.

METHODS

Sixteen patients with PD and 12 healthy matched controls were presented with stimuli that were comprised of a circular region of randomly placed dots that moved as orthographic projections of a sphere. With a normal kinetic depth effect, the Training stimuli appear as an opaque rotating ball and the Test stimuli appear as a rotating transparent ball.

RESULTS

Whereas all controls and all PD patients reported seeing the Training stimuli as a rotating ball, the patients with PD were significantly less likely to report the Test stimuli appearing as a 3D "ball" than were the healthy participants. Instead, seven PD patients often reported these bidirectional stimuli appeared "flat."

CONCLUSIONS

This study has revealed that some patients with PD have impaired spatio-temporal integration of bidirectional visual motions, but the mechanism accounting for this loss, as well as why only some patients had this deficit, needs further study. When the driver of a moving vehicle fixates upon a stationary target in the surroundings, bidirectional retinal image motions may occur. Failure to perceive 3D structure in such moving scenes can be plausibly suspected to contribute to adverse events such as auto accidents.

Rainfall simulation and Structure-from-Motion photogrammetry for the analysis of soil water erosion in Mediterranean vineyards

Soil water erosion is a serious problem, especially in agricultural lands. Among these, vineyards deserve attention, because they constitute for the Mediterranean areas a type of land use affected by high soil losses. A significant problem related to the study of soil water erosion in these areas consists in the lack of a standardized procedure of collecting data and reporting results, mainly due to a variability among the measurement methods applied. Given this issue and the seriousness of soil water erosion in Mediterranean vineyards, this works aims to quantify the soil losses caused by simulated rainstorms, and compare them with each other depending on two different methodologies: (i) rainfall simulation and (ii) surface elevation change-based, relying on high-resolution Digital Elevation Models (DEMs) derived from a photogrammetric technique (Structure-from-Motion or SfM). The experiments were carried out in a typical Mediterranean vineyard, located in eastern Spain, at very fine scales. SfM data were obtained from one reflex camera and a smartphone built-in camera. An index of sediment connectivity was also applied to evaluate the potential effect of connectivity within the plots. DEMs derived from the smartphone and the reflex camera were comparable with each other in terms of accuracy and capability of estimating soil loss. Furthermore, soil loss estimated with the surface elevation change-based method resulted to be of the same order of magnitude of that one obtained with rainfall simulation, as long as the sediment connectivity within the plot was considered. High-resolution topography derived from SfM revealed to be essential in the sediment connectivity analysis and, therefore, in the estimation of eroded materials, when comparing them to those derived from the rainfall simulation methodology. The fact that smartphones built-in cameras could produce as much satisfying results as those derived from reflex cameras is a high value added for using SfM.

Fuzzy zoning for feature matching technique in 3D reconstruction of nasal endoscopic images

3D reconstruction from nasal endoscopic images greatly supports an otolaryngologist in examining nasal passages, mucosa, polyps, sinuses, and nasopharyx. In general, structure from motion is a popular technique. It consists of four main steps; (1) camera calibration, (2) feature extraction, (3) feature matching, and (4) 3D reconstruction. Scale Invariant Feature Transform (SIFT) algorithm is normally used for both feature extraction and feature matching. However, SIFT algorithm relatively consumes computational time particularly in the feature matching process because each feature in an image of interest is compared with all features in the subsequent image in order to find the best matched pair. A fuzzy zoning approach is developed for confining feature matching area. Matching between two corresponding features from different images can be efficiently performed. With this approach, it can greatly reduce the matching time. The proposed technique is tested with endoscopic images created from phantoms and compared with the original SIFT technique in terms of the matching time and average errors of the reconstructed models. Finally, original SIFT and the proposed fuzzy-based technique are applied to 3D model reconstruction of real nasal cavity based on images taken from a rigid nasal endoscope. The results showed that the fuzzy-based approach was significantly faster than traditional SIFT technique and provided similar quality of the 3D models. It could be used for creating a nasal cavity taken by a rigid nasal endoscope.

Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras

Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints.

A trained perceptual bias that lasts for weeks

Classical (Pavlovian) conditioning procedures can be used to bias the appearance of physical stimuli. Under natural conditions this form of perceptual learning could cause perception to become more accurate by changing prior belief to be in accord with what is statistically likely. However, for learning to be of functional significance, it must last until similar stimuli are encountered again. Here, we used the apparent rotation direction of a revolving wire frame (Necker) cube to test whether a learned perceptual bias is long lasting. Apparent rotation direction was trained to have a different bias at two different retinal locations by interleaving the presentation of ambiguous cubes with presentation of cubes that were disambiguated by disparity and occlusion cues. Four groups of eight subjects were subsequently tested either 1, 7, 14, or 28 days after initial training, respectively, using a counter-conditioning procedure. All four groups showed incomplete re-learning of the reversed contingency relationship during their second session. One group repeated the counter-conditioning and showed an increase in the reverse bias, showing that the first counter-conditioning session also had a long-lasting effect. The fact that the original learning was still evident four weeks after the initial training is consistent with the operation of a mechanism that ordinarily would improve the accuracy and efficiency of perception.

Rigid Structure from Motion from a Blind Source Separation Perspective

We present an information theoretic approach to define the problem of structure from motion (SfM) as a blind source separation one. Given that for almost all practical joint densities of shape points, the marginal densities are non-Gaussian, we show how higher-order statistics can be used to provide improvements in shape estimates over the methods of factorization via Singular Value Decomposition (SVD), bundle adjustment and Bayesian approaches. Previous techniques have either explicitly or implicitly used only second-order statistics in models of shape or noise. A further advantage of viewing SfM as a blind source problem is that it easily allows for the inclusion of noise and shape models, resulting in Maximum Likelihood (ML) or Maximum a Posteriori (MAP) shape and motion estimates. A key result is that the blind source separation approach has the ability to recover the motion and shape matrices without the need to explicitly know the motion or shape pdf. We demonstrate that it suffices to know whether the pdf is sub-or super-Gaussian (i.e., semi-parametric estimation) and derive a simple formulation to determine this from the data. We provide extensive experimental results on synthetic and real tracked points in order to quantify the improvement obtained from this technique.