Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
LOCUS: Learning Object Classes with Unsupervised Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
On scene interpretation with description logics
Image and Vision Computing
Cognitive vision: The case for embodied perception
Image and Vision Computing
The visual active memory perspective on integrated recognition systems
Image and Vision Computing
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Selective visual attention enables learning and recognition of multiple objects in cluttered scenes
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Attention modulation using short- and long-term knowledge
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
IEEE Transactions on Image Processing
Creating Brain-Like Intelligence
Creating Brain-Like Intelligence
A cognitive vision system for nuclear fusion device monitoring
ICVS'11 Proceedings of the 8th international conference on Computer vision systems
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A cognitive visual system is generally intended to work robustly under varying environmental conditions, adapt to a broad range of unforeseen changes, and even exhibit prospective behavior like systematically anticipating possible visual events. These properties are unquestionably out of reach of currently available solutions. To analyze the reasons underlying this failure, in this paper we develop the idea of a vision system that flexibly controls the order and the accessibility of visual processes during operation. Vision is hereby understood as the dynamic process of selective adaptation of visual parameters and modules as a function of underlying goals or intentions. This perspective requires a specific architectural organization, since vision is then a continuous balance between the sensory stimulation and internally generated information. Furthermore, the consideration of intrinsic resource limitations and their organization by means of an appropriate control substrate become a centerpiece for the creation of truly cognitive vision systems. We outline the main concepts that are required for the development of such systems, and discuss modern approaches to a few selected vision subproblems like image segmentation, item tracking and visual object classification from the perspective of their integration and recruitment into a cognitive vision system.