Title :
Human action identification and search in video files
Author :
Mirela Kundid;Irena Galić;Daniel Vasić
Author_Institution :
Faculty of Engineering and Computing, Matice hrvatske bb, 88 000 Mostar, Bosnia and Herzegovina
Abstract :
This paper describes an approach for modeling and recognition of human actions within videos. With millions of videos that are published almost every day, there are new opportunities for research in the field of search and recognition within the video sequence. Statistical approaches and approaches based on the description of the model are described in detail in this paper and compared to a series of videos taken from various on-line databases (KTH, Weizmann, MSR-Action). There are various approaches to identify actions within video sequences. Approaches that are described within this paper are based on recognition of the action of a series of images obtained segmentation and motion picture history by constructing movement (Motion History Images MHI). In this paper we apply the technique to construct MHI on a series of images obtained from the database used for the analysis of movement in order to recognize the action within a video (greeting of human in video).
Keywords :
"Support vector machines","Hidden Markov models","Image recognition","History","Feature extraction","Training","Video sequences"
Conference_Titel :
ELMAR (ELMAR), 2015 57th International Symposium
Print_ISBN :
978-953-184-209-9
DOI :
10.1109/ELMAR.2015.7334534