中南大学学报(英文版)
中南大學學報(英文版)
중남대학학보(영문판)
JOURNAL OF CENTRAL SOUTH UNIVERSITY OF TECHNOLOGY(ENGLISH EDITION)
2015年
9期
3450-3457
,共8页
夏利民%时晓亭%涂宏斌
夏利民%時曉亭%塗宏斌
하이민%시효정%도굉빈
human activity recognition%complex activity segmentation%key frame extraction
A new method for complex activity recognition in videos by key frames was presented. The progressive bisection strategy (PBS) was employed to divide the complex activity into a series of simple activities and the key frames representing the simple activities were extracted by the self-splitting competitive learning (SSCL) algorithm. A new similarity criterion of complex activities was defined. Besides the regular visual factor, the order factor and the interference factor measuring the timing matching relationship of the simple activities and the discontinuous matching relationship of the simple activities respectively were considered. On these bases, the complex human activity recognition could be achieved by calculating their similarities. The recognition error was reduced compared with other methods when ignoring the recognition of simple activities. The proposed method was tested and evaluated on the self-built broadcast gymnastic database and the dancing database. The experimental results prove the superior efficiency.