On the Foundations of Probabilistic Relaxationwith Product Support
Journal of Mathematical Imaging and Vision
Recognition without Correspondence using MultidimensionalReceptive Field Histograms
International Journal of Computer Vision
Spatial Color Indexing and Applications
International Journal of Computer Vision
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Indexing Flower Patent Images Using Domain Knowledge
IEEE Intelligent Systems
Computer Vision and Image Understanding
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
FOCUS: a system for searching for multi-colored objects in a diverse image database
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Distinct Multicolored Region Descriptors for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Experts Organization Model for Natural Scene Images Classification
Neural Processing Letters
Discriminative cue integration for medical image annotation
Pattern Recognition Letters
Multi-modal Semantic Place Classification
International Journal of Robotics Research
Generalized sparse MRF appearance models
Image and Vision Computing
Cue integration through discriminative accumulation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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A new representation for objects with multiple colours-the colour adjacency graph (CAG)-is proposed. Each node of the CAG represents a single chromatic component of the image defined as a set of pixels forming a unimodal cluster in the chromatic scattergram. Edges encode information about adjacency of colour components and their reflectance ratio. The CAG is related to both the histogram and region adjacency graph representations. It is shown to be preserving and combining the best features of these two approaches while avoiding their drawbacks. The proposed approach is tested on a range of difficult object recognition and localisation problems involving complex imagery of non-rigid 3D objects under varied viewing conditions with excellent results.