Person re-identification is now one of the most topical and intensively studied problems in computer vision due to its challenging nature and its critical role in underpinning many multi-camera surveillance tasks. A fundamental assumption in almost all existing reidentification research is that cameras are in fixed emplacements, allowing the explicit modelling of camera and inter-camera properties in order to improve re-identification. In this paper, we present an introductory study pushing re-identification in a different direction: re-identification on a mobile platform, such as a drone. We formalise some variants of the standard formulation for re-identification that are more relevant for mobile re-identification. We introduce the first dataset for mobile reidentification, and we use this to elucidate the unique challenges of mobile re-identification. Finally, we re-evaluate some conventional wisdom about re-id models in the light of these challenges and suggest future avenues for research in this area.
CITATION STYLE
Layne, R., Hospedales, T. M., & Gong, S. (2015). Investigating open-world person re-identification using a drone. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8927, pp. 225–240). Springer Verlag. https://doi.org/10.1007/978-3-319-16199-0_16
Mendeley helps you to discover research relevant for your work.