Titlebook: Robot Vision; Second International Gerald Sommer,Reinhard Klette Conference proceedings 2008 Springer-Verlag Berlin Heidelberg 2008 3D visi

entrance

Modeling and Tracking Line-Constrained Mechanical Systemsc equations increases rapidly when studied analytically. In this work, we suggest to avoid this kind of analytic integration of interconnection constraints and instead to model them numerically via soft constraints.

Spinal-Tap

Stereo Vision Local Map Alignment for Robot Environment Mapping searching explicit correspondences between primitives. From objects found by the stereo head, an object probability density distribution is built. Then, the Gauss-Newton algorithm is used to match correspondences, so that, no explicit correspondences are needed.

津贴

Iterative Low Complexity Factorization for Projective Reconstructionw algorithm that yields the same solution using only matrices of . size irrespective of the number of frames or points. We demonstrate the superior performance of our algorithm, using synthetic and real video images.

异端

Accurate Image Matching in Scenes Including Repetitive Patternsnt. We then find matches between the points in the remained regions of the two images using the informations of the detected matches. The advantage of our method is to use an efficient matching information in the repetitive patterns. We show the effectiveness of our method by real image examples.

Preamble

entail

Emg827

Affectation

拖债

Integrating Disparity Images by Incorporating Disparity Ratetime, and also provides speed information at each pixel without using optical flow. This simple approach leads to good experimental results for real stereo sequences, by showing an improvement over previous methods.

Enliven

Towards Optimal Stereo Analysis of Image Sequencese stereo correspondences are integrated over time. Finally, an optimal fusion of stereo and optical flow, called 6D-Vision, is described that directly estimates position and motion of tracked features, even if the observer is moving. This eases the detection and tracking of moving obstacles significantly.