Score oriented Viterbi search in sport video structuring using HMM and segment models

A key question in video indexing is the effective use of all the possible sources of information. Hidden Markov models (HMM) and segment models (SM) provide powerful frameworks for audiovisual integration and structure knowledge encoding. However, incorporating punctual symbolic information, such as inlaid score labels, with these models is not straightforward. We demonstrate that using the score labels as an additional feature is not efficient and propose a novel algorithm to efficiently incorporate the score information in the Viterbi decoding process. This score oriented Viterbi search guarantees an optimal solution consistent with the available score information. Experimental results demonstrate the effectiveness of the method and its robustness to inlaid score detection errors