Computer and Robot Vision Lab Robot in the hallway The Computer Science department at Redeemer University College is active in research related to computer and robot vision. This research is being pursued by Dr. Derek Schuurman with help from students and with funding provided by NSERC.

One area of my research has focused on subspace vision techniques which operate by "learning" the appearance or position of an object and therefore do not rely on having predefined models. Much of this work involves improving the robustness of subspace vision systems in the presence of occlusions. In the case of a mobile robot, the appearance in subspace can be used to perform robot localization or to locate landmarks.

Another area of interest to me is Support Vector Machines (SVMs). Some of my recent research has explored the use of SVMs for classifying objects or obstacles in an image. Given a data set, an SVM attempts to identify a hyperplane which separates different classes of data. The hyperplane is then used as a classification boundary to predict which class to which a data point belongs. The SVM provides a powerful tool for pattern recognition in a variety of computer vision applications. One application which has been explored in our research is the use of SVMs to identify obstacles for mobile robots.

Robot in the lab Some of my recent research has explored the use of FPGAs (Field Programmable Gate Arrays) for computer vision. The large amount of data and computations in computer vision applications can present a challenge for conventional microcomputers. Performing real-time image processing on a typical video signal streaming at 60Hz can be likened to "drinking from a firehose". FPGAs can exploit the parallelism found in computer vision tasks much better than conventional CPUs. Rapidly increasing FPGA chip densities and special features and development tools have simplified the task of designing for FPGAs, making them increasingly attractive for computer vision tasks. FPGAs can be readily designed with custom parallel digital circuitry tailored for performing various image processing tasks making them well-suited for high-speed real-time vision processing systems.

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