In the infrared scene, locally adaptive regression kernels (LARK) feature has the advantage of sensitive to the change of small structure. The probability distribution of the target in the continuously adaptive mean -shift (CamShift) algorithm of single target tracking is weighted by the similarity of feature global matching . It can weaken the interference of background. In order to robustly track infrared target with shape changes, global matching is turned into local statistical matching according to the invariance of target local structure. The number of similar characteristics in the area around a point is used as the weights.
KEYWORDS: Skin, Principal component analysis, Image processing, RGB color model, Cameras, Data processing, Statistical modeling, Motion models, 3D modeling, Tablets
A tablet computer with a depth camera and a color camera is loaded on a traditional shopping cart. The inside information of the shopping cart is obtained by two cameras. In the shopping cart monitoring field, it is very important for us to determine whether the customer with goods in or out of the shopping cart. This paper establishes a basic framework for judging empty hand, it includes the hand extraction process based on the depth information, process of skin color model building based on WPCA (Weighted Principal Component Analysis), an algorithm for judging handheld products based on motion and skin color information, statistical process.
Through this framework, the first step can ensure the integrity of the hand information, and effectively avoids the influence of sleeve and other debris, the second step can accurately extract skin color and eliminate the similar color interference, light has little effect on its results, it has the advantages of fast computation speed and high efficiency, and the third step has the advantage of greatly reducing the noise interference and improving the accuracy.
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