Advances in Computational Stereo

Optimizing Disparity Candidates Space in Dense Stereo Matching

In this paper, a new approach for optimizing disparity candidates space is proposed for the solution of dense stereo matching problem. The main objectives of this approachare the reduction of average number of disparity candidates per pixel with low computational cost and high assurance of retaining the correct answer. These can be realized due to the effective use of multiple radial windows, i...

Simulation and Real-time Visualization of Changing Baseline in a Stereo Pair

The benefits of photogrammetry from low baseline stereo pairs have been increasingly demonstrated in recent years by engineers at the French Space Agency (CNES) and their collaborators, thanks to new advances in image restoration and computer vision. Such an emerging technology requires new tools for generating test data, evaluating and visualizing results. This article discusses the mathematic...

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer...

Advances in Photometric Stereo

Attention in Stereo Vision: Implications for Computational Models of Attention

The stereo correspondence problem is a topic that has been the subject of considerable research effort. What has not yet been considered is an analogue of stereo correspondence in the domain of attention. In this chapter we bring this problem to light revealing important implications for computational models of attention and in particular how these implications constrain the problem of computat...