Video Object Tracking Using MeanShift Algorithm with Semi-Automatic Implementation
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Resource Overview
Implementation of moving object tracking in video sequences using the MeanShift algorithm. Features manual target region selection via MATLAB's imcrop function for semi-automatic tracking, including algorithmic workflow and key function explanations.
Detailed Documentation
In video object tracking applications, the MeanShift algorithm serves as an effective method for following moving targets. To achieve semi-automatic tracking, we employ MATLAB's imcrop function for manual initialization of the target region. This approach involves capturing the target's initial histogram distribution through imcrop, which then serves as the reference model for the MeanShift iterative process. The algorithm continuously computes the Bhattacharyya coefficient between the target model and candidate regions, shifting the search window toward the gradient ascent direction of the probability density function. This implementation ensures accurate trajectory following by updating the target's position and scale in each frame through histogram backprojection and centroid calculation, effectively handling moderate appearance changes and occlusions.
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