The work presented in this paper aims at reducing the semantic gap between low level video features and semantic video objects. The proposed method for finding associations betwee...
In recent years, content-based image retrieval has become more and more important in many application areas. Similarity retrieval is inherently a very demanding process, in partic...
We present a novel similarity measure for bag-of-words type large scale image retrieval. The similarity function is learned in an unsupervised manner, requires no extra space over ...
The Carnegie Mellon University Informedia group has enjoyed consistent success with TRECVID interactive search using traditional storyboard interfaces for shot-based retrieval. Fo...
We analyse the kinematics of probabilistic term weights at retrieval time for di erent Information Retrieval models. We present four models based on di erent notions of probabilis...