A General Method for Appearance-Based People Search Based on Textual Queries
Person re-identification consists of recognising a person appearing in different video sequences, using an image as a query. We propose a general approach to extend appearance-based re-identification systems, enabling also textual queries describing clothing appearance (e.g., “person wearing a white shirt and checked blue shorts”). This functionality can be useful, e.g., in forensic video analysis, when textual descriptions of individuals of interest given by witnesses are available, instead of images. Our approach is based on turning any given appearance descriptor into a dissimilarity-based one. This allows us to build detectors of the clothing characteristics of interest using supervised classifiers trained in a dissimilarity space, independently on the original descriptor. Our approach is evaluated using the descriptors of three different re-identification methods, on a benchmark data set.
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