Abstract
In this paper, we present a new spatiotemporal visual attention system. Typical feature integration model is expanded to incorporate motion in our suggested system, and is able to respond to motion stimulus by employing motion fields map as one of temporal features. Proposed system is based on bottom-up approach of human visual attention, but the main difference lies in its temporal feature extraction method, and integration method of multiple spatial and temporal features. Spatial features are integrated into spatial saliency map by weighted combination method. Temporal feature is extracted by SIFT and is analyzed and reorganized into temporal saliency map. Finally, dynamic fusion technique applied to make one spatiotemporal saliency map. To evaluate the performance of the system, we tested with various kinds of real video sequences. We also compared our system with several previous systems to validate the performance of the system.
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Choi, B.G., Cheoi, K.J. (2011). Development of a Biologically Inspired Real-Time Spatiotemporal Visual Attention System. In: Nguyen, N.T., Kim, CG., Janiak, A. (eds) Intelligent Information and Database Systems. ACIIDS 2011. Lecture Notes in Computer Science(), vol 6591. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20039-7_42
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DOI: https://doi.org/10.1007/978-3-642-20039-7_42
Publisher Name: Springer, Berlin, Heidelberg
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