ACM Computing Surveys (CSUR)
From Images to Surfaces: A Computational Study of the Human Early Visual System
From Images to Surfaces: A Computational Study of the Human Early Visual System
Digital Image Processing
Direct Recovery of Three-Dimensional Scene Geometry From Binocular Stereo Disparity
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Improved Power Cepstrum Based Stereo Correspondence Method for Textured Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Computer Graphics and Applications
Relationship Between Phase and Energy Methods for Disparity Computation
Neural Computation
Computing stereo disparity and motion with known binocular cell properties
Neural Computation
A PHYSICAL SYSTEM FOR BINOCULAR VISION THROUGH SACCADE GENERATION AND VERGENCE CONTROL
Cybernetics and Systems
Towards a unified visual framework in a binocular active robot vision system
Robotics and Autonomous Systems
A spatial variant approach for vergence control in complex scenes
Image and Vision Computing
Dense disparity estimation using Gabor filters and image derivatives
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Disparity estimation in a layered image for reflection stereo
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
| Hi-index | 0.14 |
Many primate visual cortex architectures have a prominent feature responsible for the mixing of left and right eye visual data: ocular dominance columns represent thin (about 5-10 minutes of arc) strips of alternating left and right eye input to the brain. It is shown that such an architecture, when operated upon with a cepstral filter, provides a strong cue for binocular stereopsis. Specifically, the vector of binocular disparity may be easily identified in the output of the (columnar based) cepstral filter. This algorithm is illustrated with application to a random dot stereogram and to natural images. The authors suggest that this provides a fast algorithm for stereo segmentation, in a machine vision context. In a biological context, it may provide a computational rationale for the existence of columnar systems with regard to both ocular mixing and other visual modalities that have a columnar architecture.