Title :
Handling Uncertainty in Video Analysis with Spatiotemporal Visual Attention
Author :
Rapantzikos, Konstantinos ; Avrithis, Yannis ; Kollias, Stefanos
Author_Institution :
Sch. of Electr. & Comput. Eng., Athens Nat. Tech. Univ.
Abstract :
In natural vision, we center our fixation on the most informative points in a scene in order to reduce our overall uncertainty about the scene and help interpret it. Even if we are looking for a specific stimulus around us, we face a great amount of uncertainty since that stimulus could be in any spatial location. Visual attention (VA) schemes have been proposed by researchers to account for the ability of the human eye to quickly fixate on informative regions. Recently, VA in images, and especially saliency-based VA, became an active research topic of the computer vision community. The proposed work provides an extension towards VA in video sequences by integrating spatiotemporal information. The potential applications include video classification, scene understanding, surveillance and segmentation
Keywords :
computer vision; feature extraction; image segmentation; image sequences; surveillance; video signal processing; computer vision; human eye; image segmentation; informative regions; natural vision; scene understanding; spatial location; spatiotemporal visual attention; surveillance; uncertainty handling; video analysis; video classification; video sequences; Application software; Computer vision; Face detection; Humans; Image segmentation; Layout; Spatiotemporal phenomena; Surveillance; Uncertainty; Video sequences;
Conference_Titel :
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
Conference_Location :
Reno, NV
Print_ISBN :
0-7803-9159-4
DOI :
10.1109/FUZZY.2005.1452395