In video-surveillance, person reidentification is the task of recognising whether an individual has already been observed over a network of cameras. Typically, this is achieved by exploiting the clothing appearance, as classical biometric traits like the face are impractical in real-world video surveillance scenarios. Clothing appearance is represented by means of low-level local and/or global features of the image, usually extracted according to some partbased body model to treat different body parts (e.g. torso and legs) independently. This paper provides a comprehensive review of current approaches to build appearance descriptors for person re-identification. The most relevant techniques are described in detail, and categorised according to the body models and features used. The aim of this work is to provide a structured body of knowledge and a starting point for researchers willing to conduct novel investigations on this challenging topic.
Satta et al. REF provide a detailed review of appearance based descriptors for person re-identification.
Appearance Descriptors for Person Re-identification: a Comprehensive Review
ArXiv
ArXiv
Computer Science