People search with textual queries about clothing appearance attributes

Abstract

Person re-identification consists of searching for an individual of interest in video sequences acquired by a camera network, using an image of that individual as a query. Here we consider a related task, named people search with textual queries, which consists of searching images of individuals that match a textual description of clothing appearance, given by a Boolean combination of predefined attributes. People search can be useful in applications like forensic video analysis, where the query can be obtained from a eyewitness report. We propose a general method for implementing people search as an extension of any given re-identification system that uses any multiple part-multiple component appearance descriptor. In our method, the same descriptor of the re-identification system at hand is used, and attributes are chosen by taking into account the information it provides. The original descriptor is then transformed into a dissimilarity one. Attribute detectors are finally constructed as supervised classifiers, using dissimilarity descriptors as the input feature vectors. We experimentally evaluate our method on a benchmark re-identification dataset.