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Proceedings Paper

A bio-inspired system for spatio-temporal recognition in static and video imagery
Author(s): Deepak Khosla; Christopher K. Moore; Suhas Chelian
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Paper Abstract

This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

Paper Details

Date Published: 27 April 2007
PDF: 8 pages
Proc. SPIE 6560, Intelligent Computing: Theory and Applications V, 656002 (27 April 2007); doi: 10.1117/12.719975
Show Author Affiliations
Deepak Khosla, HRL Labs. LLC (United States)
Christopher K. Moore, HRL Labs. LLC (United States)
Suhas Chelian, HRL Labs. LLC (United States)

Published in SPIE Proceedings Vol. 6560:
Intelligent Computing: Theory and Applications V
Kevin L. Priddy; Emre Ertin, Editor(s)

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