John Tsotsos held a talk ot MODVis 2015, titled “Putting Saliency in its Place”. The role of attention and the place within the visual processing stream where the concept of saliency has been situated is critically examined by considering the experimental evidence and performing tests that link experiment to computation.
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Abstract: The Selective Tuning (ST) model (Tsotsos, 1995) proposed that the visual focus of attention is accompanied by a suppressive surround in spatial and feature dimensions. Follow-up studies have provided
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“Towards the quantitative evaluation of visual attention models” by Z. Bylinskii, E.M. DeGennaro, R. Rajalingham, H. Ruda, J. Zhang, J.K. Tsotsos has been accepted in Vision Research.
Read MoreWe are excited to announce that Markus Solbach joined the lab this May. After completing his Master of Science from University of Koblenz-Landau in Computer Science, he will continue his PhD studies in Computer Science and will continue to work on active vision in robotics.
Read MoreA. Rasouli and J. K. Tsotsos,“Integrating three mechanisms of visual attention for active visual search,” In 8th International Symposium on Attention in Cognitive Systems IROS, Hamburg, Germany, Sep. 2015. Bonin-Font, F., Pep Lluis Negre Carrasco, A., Solbach, M., Oliver, G. Stereo SLAM for Robust Dense 3D Reconstruction of Underwater Environments. In MTS/IEEE Oceans, Genoa, 2015. […]
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The paper “On Computational Modeling of Visual Saliency: Examining What’s Right, and What’s Left” was recently accepted for an upcoming special issue on computational models of visual attention in the Journal of Vision Research. The principal author is Neil D. B. Bruce, with contributions by Calden Wloka, Nick Frosst, Shafin Rahman, and John K. Tsotsos. […]
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Nick will be working on machine learning at the Seattle office for the summer of 2015.
Read MoreKotseruba, Y., & Tsotsos, J. (2014). Visual Attention in Dynamic Environments and its Application to Playing On-line Games. Journal of Vision, 14(10), 523-523. Rasouli A. and Tsotsos J.K, Attention in Autonomous Robotic Visual Search, in Proc. i-SAIRAS, Montreal, Quebec, Jun. 2014. Rasouli A. and Tsotsos J.K., Visual Saliency Improves Autonomous Visual Search, in Proc. The […]
Read MoreAndreopoulos, A., Tsotsos, J.K., 50 Years of Object Recognition: Directions Forward, Computer Vision and Image Understanding, Vol.117, Issue 8, August 2013, p. 827-891. Andreopoulos, A., & Tsotsos, J. K. (2013). A computational learning theory of active object recognition under uncertainty. International journal of computer vision, 101(1), 95-142. Bruce, N.D.B., Tsotsos, J.K. “Attention in Stereo Vision: […]
Read MoreAndreopoulos, A., Tsotsos, J.K., A Computational Learning Theory of Active Object Recognition Under Uncertainty, International Journal of Computer Vision , p1-48, 2012 (online August 7, 2012) Andreopoulos A., Tsotsos J.K., On Sensor Bias in Experimental Methods for Comparing Interest Point, Saliency and Recognition Algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, January 2012 (vol. […]
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