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The study proposes a method for moving object detection in multi-channel quantum video. The proposed method could detect the location of the moving target in each frame of the quantum video thereby providing a motion trail that could be used to describe the path or trajectory of the object. In validating our proposed technique, we employed a simple simulation experiment in which we detected the moving...
We propose a new object similarity measure, which can boost the performance of the mean-shift based algorithms for robust object tracking. The proposed scheme can better discriminate between different objects, compared to the commonly used measure based on Bhattacharyya coefficient optimization. The improvement is particularly noticeable when the probability distribution function of the tracked object...
Skin detection is used in applications ranging from face detection, tracking body parts and hand gesture analysis, to retrieval and blocking objectionable content. For robust skin segmentation and detection, we investigate color classification based on random forest. A random forest is a statistical framework with a very high generalization accuracy and quick training times. The random forest approach...
A new scheme for back-projection of weights for mean shift based object tracking is proposed. Weights are calculated based on relative counts of histogram bins for each feature used in similarity assessment. A fusion scheme is proposed to combine the back-projected weights from different features, such that the dissimilarities between the object being tracked and the background are boosted. A mechanism...
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