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The University of Texas at Austin Center for Perceptual Systems Faculty

The University of Texas at Austin Center for Perceptual Systems Faculty. Psychology Duane Albrecht Les Cohen Lawrence Cormack Randy Diehl Wilson Geisler ( director ) David Gilden Todd Maddox Dennis McFadden Eyal Seidemann Brian Stankiewicz Walter Wilczynski. Electrical &

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The University of Texas at Austin Center for Perceptual Systems Faculty

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  1. The University of Texas at AustinCenter for Perceptual Systems Faculty Psychology Duane Albrecht Les Cohen Lawrence Cormack Randy Diehl Wilson Geisler (director) David Gilden Todd Maddox Dennis McFadden Eyal Seidemann Brian Stankiewicz Walter Wilczynski Electrical & Computer EngineeringJ. K. Aggarwal Alan Bovik Brian Evans Joydeep Ghosh Speech & CommunicationCraig Champlin Integrative BiologyMike Ryan Other Personnel 60 graduate students 5 post-docs 4 full-time staff Computer ScienceChandrajit Bajaj Benjamin Kuipers Risto Miikkulainen http://www.cps.utexas.edu

  2. Research Auditory Circuits • Research Centers/Labs • Pollak Lab • Focus/Problems • Bats employ a rich repertoire of complex sounds for social communication • How does the brain process, decode and represent these signals in the bat’s auditory system? • Findings/Approach • How the cues from the two ears are processed by the circuits in the auditory system

  3. Research AcousticPattern Recognition • Research Centers/Labs • Ryan Lab • Focus/Problems • Sensory basis of call recognition and preferences in túngara frogs • What is the adaptive significance of female signal preferences? • Findings/Approach • Females prefer more complex calls • Simultaneous stimulation of two auditory end-organs account for this preference

  4. Research Bootstrap Learning • Research Centers/Labs • Kuipers Lab • Focus/Problems • Future robots equipped with complex sensors more like biological systems • Develop a learning agent with a domain independent set of mathematical tools • Findings/Approach • Spatial Semantic Hierarchy (SSH) provides the target for this learning process [Kuipers, AIJ, 2000]

  5. Research Eye Movements • Research Centers/Labs • Texas Eye-Movement Research Laboratory (TERL) • Focus/Problems • Human and robotic eye movements • Tools • Video eye trackers with image stabilizers • Foveated, binocular, robotic vision system to study artificial vision systems incorporating human like foveation

  6. Research Visual Search • Research Centers/Labs • Gilden lab • Focus/Problems • sensitivity to motion direction • Is rotation sensitivity a serial or parallel process? • Findings • Rotation difficult to sense with multiple (rotating) objects • Translation direction (left-right) easily sensed

  7. Research Discrimination Images • Research Centers/Labs • Texas Eye-Movement Research Laboratory (TERL) • Focus/Problems • What draws the eye? • How we decide where to look? • Findings/Approach • Subject searches for a target embedded in noise • Noise around each fixation point averaged to form a discrimination image [Beard & Ahumada, 1998] Demo at http://live.ece.utexas.edu/research/nat_stats/natural_stats.htm

  8. Research Natural ImageStatistics • Research Centers/Labs • Geisler Lab • Focus/Problems • Measure the statistical properties of natural stimuli • Relationship with design of perceptual systems? • Findings/Approach • Established statistics of natural images relevant for contour grouping [Geisler, Perry, Super & Gallogly, 2001]

  9. Research Space Variant Imaging • Research Centers/Labs • CPS Space Variant Imaging • Laboratory for image and video engineering (LIVE) • Laboratory for Artificial Neural Systems • Focus/Problems • Foveated imaging • Findings/Approach • Foveation for data compression and low-bandwidth video communications • Real-time algorithms and software for creating arbitrary space-variant video displays

  10. Research Foveated VideoCompression • Problem:Control transmission rate,buffer size, and subjective quality • Goal:Use nonuniform sampling of fovea • Retina resolution falls off 1/r2 away from fovea • Need point(s) of focus for observer(s) • Solutions:Given foveation points, • Preprocessing: apply spatially-varyinglinear filter w/ cutoff freq. proportionalto local bandwidth (no change to codec) • Modify encoder: foveation by modifyingDCT quantization tables (no change to decoder) Demo at http://live.ece.utexas.edu/research/foveated_video/demo.html

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