Statement of Research Interests

نویسنده

  • DIBYENDU NANDY
چکیده

My research interests are in machine perception, particularly the representation, analysis and interpretation of visual and auditory signals. Research in vision and audition is becoming more signiicant in an increasingly computerized world. Artiicial vision and hearing are the technologies that will enable computers to interact more naturally with humans. My interest in machine perception arises from a desire to realize this vision: to design systems that can understand and interpret images and sounds as well as people do. Visual and auditory perceptual and recognition tasks depend on being able to robustly identify such signals invariant to naturally occurring distortions, noise and clutter. The underlying representation of the information that we seek strongly innuences how the perceptual task is carried out. Consequently, a good representation should be able to capture the generic properties of the class of signals to be recognized. For instance, identifying a human in an image or image sequence is important in an application like automated surveillance. For this, we have to deene a generic and robust representation of humans and design algorithms that can successfully extract and identify such representations from image and video. The concept of what is a human has to be reinterpreted in the signal domain to try and identify the appearance of humans in images invariant to distortion due to viewpoint, motion, illumination and in cluttered and perhaps unknown backgrounds. Such a representation must provide a strong logical link between the signal domain and the conceptual domain. A signiicant part of my work is based on the modeling of human sensory perception in vision and audition. In my research, I have included connectionist ideas from neurophysiology while basing my methods on fundamental signal processing and image analysis algorithms. The focus has been on studying and utilizing eeective methods of representation and recognition of spatial percepts in audition and vision. The models developed in my research are based on common underlying representation and processing principles. My belief is that these principles need to be incorporated to generate robust representation methods for machine perception algorithms. These include extraction of representations invariant to natural distortions; capability for eecient storage and retrieval; distributed and redundant representations for robustness; ability to learn and generalize with adaptive algorithms. In the area of auditory perception, we develop a model for auditory localization, which is the ability of humans to distinguish the direction of a sound source relative to the head. …

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تاریخ انتشار 2007