Autonomous robot navigation in unstructured outdoor environments is a challenging area of active research. At the core of this navigation task lies the concept of identifying safe, traversable paths which allow the robot to progress toward a goal. Stereo vision is frequently exploited for autonomous navigation, but has limitations in terms of its density and accuracy in the far field. This pape...

This PhD aims at the design and implementation of real-time hardware-based stereo vision systems. Stereo vision deals with images acquired by a stereo camera setup, where the disparity between the stereo images allows depth estimation within a scene. In the first part of my research a new hardwareefficient real time disparity map computation module was developed which involved a fully parallel-...

In this paper we present a stereo vision system based on silicon retina sensors. Derived from the human vision system, these bio-inspired silicon retina sensors are a new type of imagers. Conventional optical sensors capture images at a fixed frame-rate and deliver pixel information of the sensor chip at a certain point in time. In contrast, a silicon retina optical sensor provides only intensi...

Depth perception is one of the most active research areas in computer vision. Passive stereo vision is a well known technique for obtaining 3-D depth information of objects seen by two or more video cameras from different viewpoints (Hartley & Zisserman, 2000|Brown et al., 2003). The difference of the viewpoint positions causes a relative displacement of the corresponding features in the stereo...

Stereo vision is a resource-intensive process. Nevertheless, it has evolved in many animals including mammals, birds, amphibians and insects. It must therefore convey significant fitness benefits. It is often assumed that the main benefit is improved accuracy of depth judgments, but camouflage breaking may be as important, particularly in predatory animals. In humans, for the last 150 years, st...

Estimating its ego-motion is one of the most important capabilities for an autonomous mobile platform. Without reliable ego-motion estimation no long-term navigation is possible. Besides odometry, inertial sensors, DGPS, laser range finders and so on, vision based algorithms can contribute a lot of information. Stereo odometry is a vision based motion estimation algorithm that estimates the ego...

Estimating its ego-motion is one of the most important capabilities for an autonomous mobile platform. Without reliable ego-motion estimation no long-term navigation is possible. Besides odometry, inertial sensors, DGPS, laser range finders and so on, vision based algorithms can contribute a lot of information. Stereo odometry is a vision based motion estimation algorithm that estimates the ego...

Real-time active 3D range cameras based on time-of-flight technology using the Photonic Mixer Device (PMD) can be considered as a complementary technique for stereo-vision based depth estimation. Since those systems directly yield 3D measurements, they can also be used for initializing vision based approaches, especially in highly dynamic environments. Fusion of PMD depth images with passive in...

A wide range of low level vision problems have been formulated in terms of finding the most probable assignment of a Markov Random Field (or equivalently the lowest energy configuration). Perhaps the most successful example is in the case of stereo vision. For the stereo problem, it has been shown that finding the global optimum is NP hard but good results have been obtained using a number of a...

Autonomous robot navigation in unstructured outdoor environments is a challenging area of active research. At the core of this navigation task lies the concept of identifying safe, traversable paths which allow the robot to progress toward a goal. Stereo vision is frequently exploited for autonomous navigation, but has limitations in terms of its density and accuracy in the far field. This pape...