Computer Vision System Toolbox
Computer vision often involves the tracking of moving objects in video. Computer Vision System Toolbox provides a comprehensive set of algorithms and functions for object tracking and motion estimation tasks.
Computer Vision System Toolbox provides video tracking algorithms, such as continuously adaptive mean shift (CAMShift) and Kanade-Lucas-Tomasi (KLT). You can use these algorithms for tracking a single object or as building blocks in a more complex tracking system. The system toolbox also provides a framework for multiple object tracking that includes Kalman filtering and the Hungarian algorithm for assigning object detections to tracks.
CAMShift uses a moving rectangular window that traverses the back projection of an object’s color histogram to track the location, size, and orientation of the object from frame to frame.
Computer Vision System Toolbox provides an extensible framework to track multiple objects in a video stream and includes the following to facilitate multiple object tracking:
Motion estimation is the process of determining the movement of blocks between adjacent video frames. The system toolbox provides a variety of motion estimation algorithms, such as optical flow, block matching, and template matching. These algorithms create motion vectors, which relate to the whole image, blocks, arbitrary patches, or individual pixels. For block and template matching, the evaluation metrics for finding the best match include MSE, MAD, MaxAD, SAD, and SSD.