Infant abnormal behavior detection method based on meanshift algorithm and SVM
A detection method, infant technology, applied in computing, computer components, character and pattern recognition, etc., can solve problems such as difficulty in obtaining ideal results, inaccurate prediction results, and lack of analysis of the overall movement of the whole body
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[0067] The implementation process of the present invention will be further described below in conjunction with the drawings.
[0068] Such as figure 1 As shown, the present invention provides an infant abnormal behavior detection method based on meanshift algorithm and SVM, including the following steps:
[0069] 1. Get the baby video and perform unified preprocessing.
[0070] 2. The baby video in step 1 is intercepted for 15s and named uniformly, and the images converted into frames are also named uniformly.
[0071] 3. Infant motion trajectory tracking: using the meanshift algorithm to track the baby’s limbs and the whole body motion trajectory of the frame image obtained in step 2, specifically including the following steps:
[0072] 3.1 Select the kernel function of the meanshift operator, and weight each sample point according to the distance from the center point. The kernel function we use is the Epannechnikov kernel function, and its number sequence is defined as follows:
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