Algorithms for clustering data
Algorithms for clustering data
Multimedia information retrieval: what is it, and why isn't anyone using it?
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
PEANO: pictorial enriched annotation of video
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A Semi-Automatic Video Annotation tool with MPEG-7 Content Collections
ISM '06 Proceedings of the Eighth IEEE International Symposium on Multimedia
A fully automated content-based video search engine supporting spatiotemporal queries
IEEE Transactions on Circuits and Systems for Video Technology
Dynamic pictorial ontologies for video digital libraries annotation
Workshop on multimedia information retrieval on The many faces of multimedia semantics
"Inside the bible": segmentation, annotation and retrieval for a new browsing experience
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Color features comparison for retrieval in personal photo collections
ACS'08 Proceedings of the 8th conference on Applied computer scince
Color Features Performance Comparison for Image Retrieval
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Picture extraction from digitized historical manuscripts
Proceedings of the ACM International Conference on Image and Video Retrieval
Automatic segmentation of digitalized historical manuscripts
Multimedia Tools and Applications
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Color is one of the most meaningful features used in content based retrieval of visual data. In video content based retrieval, color features computed on selected frames are integrated with other low-level features concerning texture, shape and motion in order to find clip similarities. For example, the Scalable Color feature defined in the MPEG-7 standard exploits HSV histograms to create color feature vectors. HSV is a widely adopted space in image and video retrieval, but its quantization for histogram generation can create misleading errors in classification of achromatic and low saturated colors. In this paper we propose an Enhanced HSV Histogram with achromatic point detection based on a single Hue and Saturation parameter that can correct this limitation. The enhanced histograms have proven to be effective in color analysis and they have been used in a system for automatic clip annotation called PEANO, where pictorial concepts are extracted by a clip clustering and used for similarity based automatic annotation.