Minor and Sklansky [21], and Faez et al. [22] then proposed that plotting a MEK162 msds line in the edge Inhibitors,Modulators,Libraries direction has the advantage of reducing parameter space to a two dimensional space. Scaramuzza et al. [23] developed a new algorithm which rejects non-arc segments (e.g., isolated points, noises, angular points, and straight segments) and plots lines in the direction of arc concavity. The algorithm gives more precise approximation for circle location.There are two major procedures in stereo vision tracking, including motion tracking and stereo matching [24]. The location of the desired target in the reference image (e.g., the left image) is tracked by Inhibitors,Modulators,Libraries using the motion tracking algorithm, and the stereo matching algorithm is then matching the correspondence location of the desired target in the other image (e.

g., the right image).Motion tracking involves two types of algorithms: feature-based tracking Inhibitors,Modulators,Libraries algorithm [25,26] and region-based tracking algorithm [27�C29]. The feature-based tracking algorithm tracks partial features of the target. The canny edge detector [30] is often used for extracting edge features of the target, and point feature of the target��s corner is extracted by the SUSAN corner detector [31]. Region-based tracking algorithm uses the template/block determined by user selection or image recognition to track the target. Once the template/block is decided, the algorithm starts to compute the correlation between the template/block and the designated region in the current frame. The most common used correlation criteria are the sum of absolute differences (SAD) and the sum of squared differences (SSD).

References [28,29] suggested Inhibitors,Modulators,Libraries the template update strategies that solve the GSK-3 ��drifting�� problem caused by environmental influence (e.g., light conditions or object occlusion) during motion tracking.The developed stereo matching methods can roughly be divided into two categories: local methods and global methods [32]. Although global methods, such as those using dynamic programming [33], can be less sensitive to local ambiguous regions reference 2 (e.g., occlusion regions or regions with uniform texture in an image) than those using the local method, the global methods require more computing cost [34]. Block matching [35] is the best known method among the local methods because of its efficiency and simplicity in implementation. In the block matching, the reference block determined in moving tracking is used to search stereo corresponding by using matching criteria such as SSD or SAD. Once the stereo matching is made, each corresponding locations of the target in the stereo images are found, that is, the disparity of the target��s location is known. Therefore, the depth information of the target can be calculated by triangulation.