Action identification using a descriptor with autonomous fragments in a multilevel prediction scheme. Issue 2 (February 2017)

• Record Type: Journal Article
• Authors: Alcantara, Marlon; Moreira, Thierry; Pedrini, Helio; Flórez-Revuelta, Francisco
• Is Part Of: Signal, image and video processing. Volume 11:Issue 2(2017)
• Page Start: 325
• Page End: 332
• Publication Date: 2017-02
• Subjects: Action identification -- Autonomous fragments -- Video stream -- Interest points; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-016-0940-3
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract Recent technological advances have provided powerful devices with high processing and storage capabilities. Video cameras can be found in several different areas, such as banks, schools, stores, public streets and industry for a variety of tasks. Camera technology has increasingly improved, achieving higher resolution and acquisition frame rates. Nevertheless, most video analysis tasks are performed by human operators, whose performance may be affected by fatigue and stress. To address this problem, this work proposes and evaluates a method for action identification in videos through a new descriptor composed of autonomous fragments applied to a multilevel prediction scheme. The method is very fast and achieves over 90 % of accuracy in known public data sets. The developed system allows for the current video cameras the possibility of real-time action analysis, demonstrating to be a useful and powerful tool for surveillance purpose.