Making full use of spatial-temporal interest points: An AdaBoost approach for action recognition

摘要

Although spatial-temporal interest points (STIPs) with bag of words strategy have achieved success in action recognition, they lose much information during forming histograms, especially the relations among STIPs. We propose to use effective human body regions (EHBRs) to find these relations in order to compensate for bag of spatial-temporal words (BOW). Combining bag of spatial-temporal words and EHBRs, the AdaBoost approach is used to achieve high accuracy. Experiments on benchmark dataset KTH verify our approach effectiveness and efficiency.