![[Yale seal]](/view-wwwdir_n/http://www.cs.yale.edu/HTML/YALE/VISION/1.gif)
The Yale Vision and Robotics Group
The Yale Vision and Robotics GroupThere is a broad spectrum of research activities in vision and robotics at Yale. The members of this group include faculty from Computer Science, Electrical Engineering, Psychology, Neuroscience, and the Yale Medical School. Active areas of research include motion analysis, neural network-based recognition, geometric reasoning, human and computer object recognition, mobile robotics, sensor-based manipulation, control of highly dynamic nonlinear systems, and planning. Students interested in interdisciplinary work in these and related areas are especially encouraged to apply.
Find out more about my research on task-directed robotics and visual servoing
Sensor-based decision making and planning, and in particular, "task-directed" sensing and the incorporation of "resource constraints" in sensor data interpretation. Visual servoing and hand-eye coordination.
Find
out more about my research on visually guided robotics and object
recognition
Perception for robotics, and in particular, computer vision, model based recognition of curved objects, and autonomous mobile robot navigation.
Find
out more about my research on human visual cognition
Behavioral, computational, and neuroscientific approaches to visual cognition, and in particular, the multiple-views approach to human object recognition. Related interests include mental imagery, motion perception, visual attention, perceptual categorization, and spatial language.
Geometrically- and physically-based models and mathematical optimization-based decision strategies to analyze biomedical images. Reinforcement of local curvilinear structure using a parametrized form of relaxation labeling, locating bounding contours and surfaces of anatomical objects from image data using a parametrically deformable approach, motion tracking of non-rigid objects using differential geometric features, and the integration of visual modules using a game theoretic approach.
Director, Intelligent Sensors Laboratory. Current interests include applying of biological sensorimotor principles to robotic systems, extracting information from sonar signals for acoustic vision, and investigating the inverse problem of determining source parameters from measurements.
R. Kuc & B. Barshan, "Bat-like sonar for guiding mobile robots", IEEE Control Systems Magazine, August, 1992.
R. Kuc & V. B. Viard, "A physically based navigation strategy for sonar-guided vehicles", Int. J. Robotics Research, Vol. 10, 1991.
S. Morse, D. Q. Mayne, & G. C. Goodwin, "Applications of hysteresis switching in parameter adaptive control", IEEE Trans. Auto. Control, Vol. 37, September, 1992, pp. 1343-1354.
S. Morse & F. M. Pait, "A cyclic switching strategy for parameter-adaptive control", Proc. 1992 IEEE Conf. on Decision and Control, Tucson, December, 1992.
"Dwell-time Switching", Second European Control Conference, Groningen, The Netherlands, June 1993.
Objective functions defined on mixed (binary and continuous) variables frequently arise in a Bayesian maximum a posteriori (MAP) context. My work focuses on designing deterministic, continuation methods for optimizing these objective functions. The application areas are tomographic reconstruction in medical imaging, inexact model matching in vision and deterministic annealing in combinatorial optimization.
The application of geometric and physical properties of objects to computer vision. Characterization of local and global geometry of rigid and non-rigid objects and the recovery of these characteristics from images. Applied to medical images, robotic images, and image databases. Investigation of physical reflectance models and their application to 3-D reconstruction of surface shape from shading and photometric stereo.
Facilities
Sun Microsystems SPARC workstations; Silicon Graphics Workstations; several parallel computational systems; many Apple Macintoshes and MS DOS PCs; several microcomputer-based platforms for use in psychophysical studies; three direct drive robotic arms; a Zebra Zero robot arm; a fully equipped teaching laboratory for robotics; a transputer-based mobile robot system; a Nomad 200 mobile robot; digital imaging equipment; extensive software libraries for image processing, 2D and 3D graphics, animation, simulation, program development, and document prepartion.
Computer Science Gregory D. Hager Drew McDermott hager@cs.yale.edu mcdermott@cs.yale.edu (203) 432-6432 (203) 432-1223 Anand Rangarajan Hemant Tagare rangarajan-anand@cs.yale.edu tagare-hemant@cs.yale.edu (203) 432 1285 (203) 432-6429 Electrical Engineering David J. Kriegman James S. Duncan kriegman@yale.edu duncan@venus.ycc.yale.edu (203) 432-4091 (203) 785-6322 Roman Kuc Stephen Morse roman@tryzub.eng.yale.edu morse@sysc.eng.yale.edu (203) 432-4291 (203) 432-4295 Diagnostic Radiology Amir Amini Lawrence Staib amini@noodle.med.yale.edu staib@noodle.med.yale.edu (203) 785-7085 (203) 785-5958 Psychology Michael J. Tarr tarr@cs.yale.edu (203) 432-4637
Graduate School Admissions Yale University P.O. Box 1504A Yale Station New Haven, CT 06520-7425 Completed applications are due January 2.