计算机应用与软件2024，Vol.41Issue(4)：179-184,6.DOI:10.3969/j.issn.1000-386x.2024.04.027
基于动态时空信息融合的视频行为识别
VIDEO BEHAVIOR RECOGNITION BASED ON DYNAMIC SPATIOTEMPORAL INFORMATION FUSION
摘要
Abstract
Video data has complex and redundant information in time and space dimensions.In order to solve this problem,we designed a motion module.This module calculated the temporal and spatial differences between pixels based on time and space features.The dynamic spatiotemporal differences were decomposed into two branches for processing.One branch was used to correct the temporal and spatial displacements on adjacent frames,and the other one was used to capture contextual information at adjacent moments.In the time interval of adjacent frames,the temporal and spatial probability distribution of pixels was modeled.The results show that the motion module improves the performance of video recognition while slightly affecting flops and parameters.Its effectiveness and efficiency was verified on public datasets.关键词
深度学习/时空特征/特征融合/行为识别Key words
Deep learning/Spatiotemporal features/Feature fusion/Behavior recognition分类
计算机与自动化引用本文复制引用
史亚琪,赵峰..基于动态时空信息融合的视频行为识别[J].计算机应用与软件,2024,41(4):179-184,6.基金项目
广西重点研发计划项目(桂科AB19110044). （桂科AB19110044）
