Efficient sketch recognition based on shape features and multidimensional indexing

Face sketch recognition on real forensic mug shot photo galleries is a complex task since a large amount of images needs to be matched in few seconds to produce a useful outcome. Several effective solutions for sketch-based subject identification have been recently proposed, but the cost of linear search makes them not scalable when large databases have to be scanned. In this work we propose an approach which combines the use of efficient shape features for sketch-photo matching with a suitable indexing structure based on dimensionality reduction. The proposed method provides a preliminary set of candidate photos to be used as input for the final identification based on state-of-the-art techniques, offering scalability and time efficiency without noticeably compromising recognition accuracy, as confirmed by the experimental results.