Perceptual organization and the representation of natural form
Artificial Intelligence
The cycle of uncertainty and constraint in robot perception
Proceedings of the 4th international symposium on Robotics Research
Maintaining representations of the environment of a mobile robot
Proceedings of the 4th international symposium on Robotics Research
A stochastic map for uncertain spatial relationships
Proceedings of the 4th international symposium on Robotics Research
Ignorance, myopia, and naivete´ in computer vision systems
CVGIP: Image Understanding
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Perceptual organization and the curve partitioning problem
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
The role of data reprocessing in complex acoustic environments
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Computer Vision System for Modeling Human Interaction
ICVS '99 Proceedings of the First International Conference on Computer Vision Systems
3D Object Recognition and Visualization on the Web
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
A study on the manipulation of 2D objects in a projector/camera-based augmented reality environment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
VAMBAM: view and motion -based aspect models for distributed omnidirectional vision systems
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Approximate world models: incorporating qualitative and linguistic information into vision systems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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A representation paradigm for instantiating and refining multiple, concurrent descriptions of an object from a sequence of imagery is presented. It is designed for the perception system of an autonomous robot that needs to describe many types of objects, initially detects objects at a distance and gradually acquires higher resolution data, and continuously collects sensory input. Since the data change significantly over time, the paradigm supports the evolution of descriptions, progressing from crude 2-D 'blob' descriptions to complete semantic models. To control this accumulation of new descriptions, the authors introduce the idea of representation space, a lattice of representations that specifies the order in which they should be considered for describing an object. A system, TraX, that constructs and refines models of outdoor objects detected in sequences of range data is described.