关键词: 行为覆盖区, 行为核心, 多视角行为模型, 行为识别, 隐变量支持向量机

Abstract: We study the concepts of ACA (Action Coverage Area) and AC (Action Core), and design a multiple-viewpoint action model based on the advanced object recogniton method Latent SVM ( Support Vector Machine). Multi-viewpoint ACA can succinctly describe the non-rigid change and appearance variation due to different viewpoints and multi-viewpoint AC, because the auxiliary of ACA can help to improve the efficiency and robustness of action recognition. We created an independent dataset of human action for model training and testing. Experiments showed that our model had high performance in classifying and detecting human action in still images.

Key words: action core(AC),  action recognition, multiple viewpoint action model (MVAM), latent support vector machine(SVM), action coverage area (ACA)