Identification of everyday objects on the basis of kinetic contours

A systematic comparison between visual cues for boundary detection

The detection of object boundaries is a critical first step for many visual processing tasks. Multiple cues (we consider luminance, color, motion and binocular disparity) available in the early visual system may signal object boundaries but little is known about their relative diagnosticity and how to optimally combine them for boundary detection. This study thus aims at understanding how early visual processes inform boundary detection in natural scenes. We collected color binocular video sequences of natural scenes to construct a video database. Each scene was annotated with two full sets of ground-truth contours (one set limited to object boundaries and another set which included all edges). We implemented an integrated computational model of early vision that spans all considered cues, and then assessed their diagnosticity by training machine learning classifiers on individual channels. Color and luminance were found to be most diagnostic while stereo and motion were least. Combining all cues yielded a significant improvement in accuracy beyond that of any cue in isolation. Furthermore, the accuracy of individual cues was found to be a poor predictor of their unique contribution for the combination. This result suggested a complex interaction between cues, which we further quantified using regularization techniques. Our systematic assessment of the accuracy of early vision models for boundary detection together with the resulting annotated video dataset should provide a useful benchmark towards the development of higher-level models of visual processing.

Reliability and validity of the Leuven Perceptual Organization Screening Test (L-POST)

Neuropsychological tests of visual perception mostly assess high-level processes like object recognition. Object recognition, however, relies on distinct mid-level processes of perceptual organization that are only implicitly tested in classical tests. Furthermore, the psychometric properties of the existing instruments are limited. To fill this gap, the Leuven perceptual organization screening test (L-POST) was developed, in which a wide range of mid-level phenomena are measured in 15 subtests. In this study, we evaluated reliability and validity of the L-POST. Performance on the test is evaluated relative to a norm sample of more than 1,500 healthy control participants. Cronbach's alpha of the norm sample and test-retest correlations for 20 patients provide evidence for adequate reliability of L-POST performance. The convergent and discriminant validity of the test was assessed in 40 brain-damaged patients, whose performance on the L-POST was compared with standard clinical tests of visual perception and other measures of cognitive function. The L-POST showed high sensitivity to visual dysfunction and decreased performance was specific to visual problems. In conclusion, the L-POST is a reliable and valid screening test for perceptual organization. It offers a useful online tool for researchers and clinicians to get a broader overview of the mid-level processes that are preserved or disrupted in a given patient.

The influence of orientation jitter and motion on contour saliency and object identification

One of the ultimate goals of vision research is to understand how some elements are grouped together and differentiated from others to form object representations in a complex visual scene. There exists an extensive literature on this grouping/segmentation problem, but most of the studies have used un-recognizable stimuli that have little to do with object recognition per se. We used Gabor-rendered outlines of real-world objects to study some relationships between bottom-up and top-down processes in both spatial- and motion form perception. We manipulated low-level properties, such as element orientation and local motion, while incorporating higher-level properties, such as object complexity and identity, and found that adding local motion improved overall performance in both object detection and object identification tasks. Adding orientation jitter effectively decreased object detection performance in both static and motion conditions, and increased reaction time for identification in the static condition. Orientation jitter had much less effect on reaction times for identification in the local motion condition than in the static condition. Both contour properties ("good continuation") and object properties (identifiability) had a positive effect on detection and reaction time for identification.