Inrecentresearchoncomputervisionsystems,attentionhasbeenplayingacrucialrolein mediatingbottom-upandtop-downpathsofinformationprocessing. Inappliedresearch, the development of enabling technologies such as miniaturized mobile sensors, video surveillance systems, and ambient intelligence systems involves the real-time analysis of enormous quantities of data. Knowledge has to be applied about what needs to be attendedto,andwhen,andwhattodoinameaningfulsequence,incorrespondencewith visual feedback. Methods on attention and control are mandatory to render computer vision systems more robust. The 2nd International Workshop on Attention and Performance in Computational Vision (WAPCV 2004) was held in the Czech Technical University of Prague, Czech Republic, as an associated workshop of the 8th European Conference on Computer - sion (ECCV 2004). The goal of this workshop was to provide an interdisciplinary forum tocommunicatecomputationalmodelsofvisualattentionfromvariousviewpoints,such as from computer vision, psychology, robotics and neuroscience. The motivation for - terdisciplinarity was communication and inspiration beyond the individual community, to focus discussion on computational modelling, to outline relevant objectives for p- formance comparison, to explore promising application domains, and to discuss these with reference to all related aspects of cognitive vision. The workshop was held as a single-day, single-track event, consisting of high-quality podium and poster presen- tions. Invited talks were given by John K. Tsotsos about attention and feature binding in biologically motivated computer vision and by Gustavo Deco about the context of attention, memory and reward from the perspective of computational neuroscience. The interdisciplinary program committee was composed of 21 internationally r- ognized researchers.
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Inrecentresearchoncomputervisionsystems,attentionhasbeenplayingacrucialrolein mediatingbottom-upandtop-downpathsofinformationprocessing. Inappliedresearch, the development of enabling technologies such as miniaturized mobile sensors, video surveillance systems, and ambient intelligence systems involves the real-time analysis of enormous quantities of data. Knowledge has to be applied about what needs to be attendedto,andwhen,andwhattodoinameaningfulsequence,incorrespondencewith visual feedback. Methods on attention and control are mandatory to render computer vision systems more robust. The 2nd International Workshop on Attention and Performance in Computational Vision (WAPCV 2004) was held in the Czech Technical University of Prague, Czech Republic, as an associated workshop of the 8th European Conference on Computer - sion (ECCV 2004). The goal of this workshop was to provide an interdisciplinary forum tocommunicatecomputationalmodelsofvisualattentionfromvariousviewpoints,such as from computer vision, psychology, robotics and neuroscience. The motivation for - terdisciplinarity was communication and inspiration beyond the individual community, to focus discussion on computational modelling, to outline relevant objectives for p- formance comparison, to explore promising application domains, and to discuss these with reference to all related aspects of cognitive vision. The workshop was held as a single-day, single-track event, consisting of high-quality podium and poster presen- tions. Invited talks were given by John K. Tsotsos about attention and feature binding in biologically motivated computer vision and by Gustavo Deco about the context of attention, memory and reward from the perspective of computational neuroscience. The interdisciplinary program committee was composed of 21 internationally r- ognized researchers.
This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Attention and Performance in Computational Vision, WAPCV 2004, held in Prague, Czech Republic in May 2004. The 16 revised full papers presented together with an invited paper were carefully selected during two rounds of reviewing and improvement. The papers are organized in topical sections on attention in object and scene recognition, architectures for sequential attention, biologically plausible models for attention, and applications of attentive vision.
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