Person re-identification with a PTZ camera: An introductory study
We present an introductory study that paves the way for a new kind of person re-identification, by exploiting a single Pan-Tilt-Zoom (PTZ) camera. PTZ devices allow to zoom on body regions, acquiring discriminative visual patterns that enrich the appearance description of an individual. This intuition has been translated into a statistical direct reidentification scheme, which collects two images for each probe subject: the first image captures the probe individual, focusing on the whole body; the second can be a zoomed body part (head, torso or legs) or another whole body image, and is the outcome of an action-selection mechanism, driven by feature selection principles. The validation of this technique is also explored: in order to allow repeatability, two novel multi-resolution benchmarks have been created. On these data, we demonstrate that our approach selects effective actions, by focusing on body portions which discriminate each subject. Moreover, we show that the proposed compound of two images overwhelms standard multi-shot descriptions, composed by many more pictures.