behavioural sciences computing; biomedical optical imaging; hidden Markov models; image classification; image segmentation; medical image processing; patient monitoring; surveillance; video signal processing; NHP behavior analysis; NHP behavior classification; NHP behavior segmentation; NHP surveillance video data; NHP-related studies; SHOOF; automated monitoring; batch recursive version; behavior class number determination; biomedical research; feature set combining local sub-block histograms of oriented optical flow; joint NHP behaviour classification method; long-term monitoring; nonhuman primates; occlusion effects; sticky HDP-HMM; sticky hierarchical Dirichlet process hidden Markov model; time segmentation; Computer vision; Hidden Markov models; Histograms; Image motion analysis; Integrated optics; Optical sensors; Surveillance; HDP-HMM; behavior classification; behavior segmentation; non-human primates; surveillance video;
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机译:加速度计数据行为分类使用代理的局限性:Caprids中使用随机林模型的精炼方法
机译:基于加权联合稀疏表示的无稳压对齐人脸识别的分类方法