Letters: Selective attention-based novelty scene detection in dynamic environments

Authors:
Sang-Woo Ban;Minho Lee
Affiliations:
Department of Information and Communication Engineering, Dongguk University,707 Seokjang-Dong, Gyeongju, Gyeongbuk 780-714, Republic of Korea;School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, Taegu 702-701, Republic of Korea
Venue:
Neurocomputing
Year:
2006

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Abstract

We propose a biologically motivated novelty detection model of a scene that can give a robust performance for natural color scenes with an affine transformed field of view, as well as noisy scenes in a dynamic visual environment. Novelty detection is an essential property for developmental robots. A topology of a visual scan path of an input scene and an energy signature for the corresponding visual scan path are obtained and considered when deciding on a novelty occurrence in an input scene. The visual scan path is generated by a low-level top-down attention model in conjunction with a bottom-up saliency map model.