Footballs Video Scene Retrieval with Interactive Genetic Algorithm

This paper proposed an interactive genetic algorithm (IGA) for football video scenes retrieval with multimodal features. Four audio-visual features (average shot duration, average motion activity average sound energy, and average speech rate) were extracted from each of the videos. Then they were encoded as chromosomes and indexed into search table. First, the proposed algorithm randomly selected the videos from the initial population of videos database, and the user selected what he (she) wanted in mind. Next, the associated chromosomes of selected videos were regarded as target chromosomes after crossover and chromosomes in the database videos were compared based on similarity function to obtain the most similar videos as solutions of the next generation. By iterating this process, a new population of videos was retrieved. This approach of retrieval shows about 84% of effectiveness on the average over 200 videos.