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meanshift tracking based on visal
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Meanshift is first proposed by comaniciu, which is an algorithm for tracking non rigid objects. In order to represent the target, we first need to select a feature space. The reference target is represented by the probability density function Q in the feature space. For example, the reference model can select the color probability density function of the target. Without losing generality, the target model can be regarded as the center of its space. In the next frame, the candidate target is defined as position Y, which is represented by probability density function p (y). In order to meet the requirement of real-time, they are represented by histogram statistics ^ Q and ^ P (y) respectively
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Meanshift tracking based on visal
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Meanshift by Comaniciu first put forward, is an algorithm for tracking non-rigid objects. In order to characterize the target, you first need to select a feature space. Reference objects, represented by the probability density function of q in the feature space, such as reference models you can choose color probability density function. Without loss of generality, it can be considered the center of the target model at the Centre of their space. Next frame candidate targets are defined as in location y, with probability density function p (y) to represent. In order to meet real-time requirements, respectively, using non-parameter histogram in ^q and ^p (y)
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Cafeteria meal card system
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This code is based on the College canteen card system, programming with the Java language. Actions include the following: deletion check modification of students ' basic information, meal card balances, recharge amount, card loss, freeze and thaw.
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