High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
VeggieVision: A Produce Recognition System
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Guide to Biometrics
Segmentation and Tracking of Multiple Humans in Crowded Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nighttime Vehicle Detection for Intelligent Headlight Control
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Tracking Multiple Occluding People by Localizing on Multiple Scene Planes
IEEE Transactions on Pattern Analysis and Machine Intelligence
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Attention-based target localization using multiple instance learning
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
A performance study of an intelligent headlight control system
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Large-scale vehicle detection in challenging urban surveillance environments
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Visual item verification for fraud prevention in retail self-checkout
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
Attribute-based vehicle search in crowded surveillance videos
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Component-based track inspection using machine-vision technology
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Machine Recognition of Human Activities: A Survey
IEEE Transactions on Circuits and Systems for Video Technology
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Humans, as well as many living organisms, are gifted with the power of "seeing" and Bunderstanding[ the environment around them using their eyes. The ease with which humans process and understand the visual world is very deceiving and often prompts us to underestimate the effort and methods needed to build practical, effective, and inexpensive computer vision systems. In essence, humans have a 500-million-year head start due to evolution; it is extremely difficult at this point to build a computer vision system that has the abilities of a three-year-old child. However, by confining ourselves to particular domains, we can often find shortcuts to solve particular problems. This paper illustrates a number of such solutions in various areas developed by our group at IBM. These include object finding for video surveillance, person identification via biometrics, inspection of manufactured items along railways, and scene understanding for driver assistance, as well as object recognition and motion interpretation for retail stores. We discuss the real-world constraints for each system and describe how we overcame the irksome variability inherent in each task. By further analyzing such successful systems and comparing them to each other, we can come to understand the common underlying problems and thus start to extend our initially limited areas of competence into a more general-purpose vision toolkit. This paper concludes with a set of challenging unresolved problems that if solved could spur great progress in practical computer vision.