The identification and tracking for model pigs, as a vital research content for studying the habits of model pigs, drawed more and more considerable attention. To fulfill people requirements for the effectiveness of the non-significant model pig tracking in breeding environment, a Camshift tracking approach based on correlation probability graph, i.e., CamTracor_−PG, is proposed in this paper, in which the correlation probability graph is introduced to achieve target positioning and tracking. Technically, acquiring images through a vision sensor, according to the circular arrangement of pixels in the inverse probability projection graph, and multiplying the inverse projection probability value of a pixel by its surrounding pixels could obtain the weighted sum. Then, the target projection grayscale graph is established by utilizing the correlation probability value for positioning, identification, and tracking of model pigs. Finally, extensive experiments are conducted to validate reliability and efficiency of our approach.

识别和跟踪模型猪作为研究模型猪习性的重要研究内容，引起了越来越多的关注。为了满足人们对繁殖环境中非重要模型猪跟踪有效性的要求，基于相关概率图的Camshift跟踪方法，即C a m T r a c o r _{- P G}本文提出了，其中引入了相关概率图以实现目标定位和跟踪。从技术上讲，通过视觉传感器根据逆概率投影图中像素的圆形排列获取图像，并将像素的逆投影概率值与其周围像素相乘即可得到加权和。然后，利用相关概率值对模型猪进行定位，识别和跟踪，建立目标投影灰度图。最后，进行了广泛的实验以验证我们方法的可靠性和效率。