Motion analysis from first-order properties of optical flow
CVGIP: Image Understanding - Special issue on purposive, qualitative, active vision
Face recognition: the problem of compensating for changes in illumination direction
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Integration and control of reactive visual processes
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Driving saccade to pursuit using image motion
International Journal of Computer Vision
A framework for modeling and verifying visually guided agents: design, analysis and experiments
A framework for modeling and verifying visually guided agents: design, analysis and experiments
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
X Vision: a portable substrate for real-time vision applications
Computer Vision and Image Understanding
Digital Image Warping
Multi-Modal Tracking of Faces for Video Communications
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Gesture recognition using the Perseus architecture
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Journal of Cognitive Neuroscience
An Incremental Learning Algorithm for Face Recognition
ECCV '02 Proceedings of the International ECCV 2002 Workshop Copenhagen on Biometric Authentication
Detection of Frontal Faces in Video Streams
ECCV '02 Proceedings of the International ECCV 2002 Workshop Copenhagen on Biometric Authentication
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In this paper, a basic conceptual architecture aimed at the design of Computer Vision System is qualitatively described. The proposed architecture addresses the design of vision systems in a modular fashion using modules with three distinct units or components: a processing network or diagnostics unit, a control unit and a communications unit. The control of the system at the modules level is designed based on a Discrete Events Model. This basic methodology has been used to design a real-time active vision system for detection, tracking and recognition of people. It is made up of three functional modules aimed at the detection, tracking, recognition of moving individuals plus a supervision module. The detection module is devoted to the detection of moving targets, using optic flow computation and relevant areas extraction. The tracking module uses an adaptive correlation technique to fixate on moving objects. The objective of this module is to pursuit the object, centering it into a relocatable focus of attention window (FOAW) to obtain a good view of the object in order to recognize it. Several focus of attention can be tracked simultaneously. The recognition module is designed in an opportunistic style in order to identify the object whenever it is possible. A demonstration system has been developed to detect, track and identify walking people.