Quantitative Landscape Assessment Using LiDAR and Rendered 360° Panoramic Images

QUANTITATIVE VIEW ASSESSMENT (QUVIAS) METHOD FOR WINDOW VISIBILITY ANALYSIS UTILIZING BIM, GIS AND WEB ENVIRONMENTS

The developers of the construction project assess the economic feasibility of the project at the early stages of project development and analyse possible alternative solutions. This research focuses on the assessment of property attractiveness and building location problems at an early stage of project development and proposes the original method for visibility analysis based on the utilization of Building Information Modelling (BIM), Geographic Information System (GIS) and Web environments. The proposed Quantitative View Assessment (QUVIAS) method allows to assess the view mathematically and presents it as a quantitative parameter. The proposed method considers the mathematical shape of the view as a sphere and utilizes spherical coordinates that remove distortions and increase the accuracy of the analysis. The presented approach determines quantitative view coefficients for alternatives of windows, premises and buildings, including their comparison. The way of determining the view proposed in the QUVIAS method can help decision-makers to make more accurate decisions during the selection of a project development strategy. The experimental analysis proved the usefulness of the proposed QUVIAS method in the assessment of the rational building location and prediction of project revenues as well as potential usefulness in the estimation of property attractiveness.

Sky and Ground Segmentation in the Navigation Visions of the Planetary Rovers

Sky and ground are two essential semantic components in computer vision, robotics, and remote sensing. The sky and ground segmentation has become increasingly popular. This research proposes a sky and ground segmentation framework for the rover navigation visions by adopting weak supervision and transfer learning technologies. A new sky and ground segmentation neural network (network in U-shaped network (NI-U-Net)) and a conservative annotation method have been proposed. The pre-trained process achieves the best results on a popular open benchmark (the Skyfinder dataset) by evaluating seven metrics compared to the state-of-the-art. These seven metrics achieve 99.232%, 99.211%, 99.221%, 99.104%, 0.0077, 0.0427, and 98.223% on accuracy, precision, recall, dice score (F1), misclassification rate (MCR), root mean squared error (RMSE), and intersection over union (IoU), respectively. The conservative annotation method achieves superior performance with limited manual intervention. The NI-U-Net can operate with 40 frames per second (FPS) to maintain the real-time property. The proposed framework successfully fills the gap between the laboratory results (with rich idea data) and the practical application (in the wild). The achievement can provide essential semantic information (sky and ground) for the rover navigation vision.

Panoramic Mapping with Information Technologies for Supporting Engineering Education: A Preliminary Exploration

The present researchers took multistation-based panoramic images and imported the processed images into a virtual tour platform to create webpages and a virtual reality environment. The integrated multimedia platform aims to assist students in a surveying practice course. A questionnaire survey was conducted to evaluate the platform’s usefulness to students, and its design was modified according to respondents’ feedback. Panoramic photos were taken using a full-frame digital single-lens reflex camera with an ultra-wide-angle zoom lens mounted on a panoramic instrument. The camera took photos at various angles, generating a visual field with horizontal and vertical viewing angles close to 360°. Multiple overlapping images were stitched to form a complete panoramic image for each capturing station. Image stitching entails extracting feature points to verify the correspondence between the same feature point in different images (i.e., tie points). By calculating the root mean square error of a stitched image, we determined the stitching quality and modified the tie point location when necessary. The root mean square errors of nearly all panoramas were lower than 5 pixels, meeting the recommended stitching standard. Additionally, 92% of the respondents (n = 62) considered the platform helpful for their surveying practice course. We also discussed and provided suggestions for the improvement of panoramic image quality, camera parameter settings, and panoramic image processing.

Automatic 360° Mono-Stereo Panorama Generation Using a Cost-Effective Multi-Camera System

In recent years, 360° videos have gained the attention of researchers due to their versatility and applications in real-world problems. Also, easy access to different visual sensor kits and easily deployable image acquisition devices have played a vital role in the growth of interest in this area by the research community. Recently, several 360° panorama generation systems have demonstrated reasonable quality generated panoramas. However, these systems are equipped with expensive image sensor networks where multiple cameras are mounted in a circular rig with specific overlapping gaps. In this paper, we propose an economical 360° panorama generation system that generates both mono and stereo panoramas. For mono panorama generation, we present a drone-mounted image acquisition sensor kit that consists of six cameras placed in a circular fashion with optimal overlapping gap. The hardware of our proposed image acquisition system is configured in such way that no user input is required to stitch multiple images. For stereo panorama generation, we propose a lightweight, cost-effective visual sensor kit that uses only three cameras to cover 360° of the surroundings. We also developed stitching software that generates both mono and stereo panoramas using a single image stitching pipeline where the panorama generated by our proposed system is automatically straightened without visible seams. Furthermore, we compared our proposed system with existing mono and stereo contents generation systems in both qualitative and quantitative perspectives, and the comparative measurements obtained verified the effectiveness of our system compared to existing mono and stereo generation systems.