Sports Video Annotation Using Enhanced HSV Histograms in Multimedia Ontologies

This paper presents multimedia ontologies, where multimedia data and traditional textual ontologies are merged. A solution for their implementation for the soccer video domain and a method to perform automatic soccer video annotation using these extended ontologies is shown. 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 more general concepts of the sport domain (e.g. play/break, crowd, etc.) are put in correspondence with the more general visual features of the video like color and texture, while the more specific concepts of the soccer domain (e.g. highlights such as attack actions) are put in correspondence with domain specific visual feature like the soccer playfield and the players. Experimental results for annotation of soccer videos using generic concepts are presented.