Person reidentification using deep foreground appearance modeling

Appearance-based person reidentification in camera networks: problem overview and current approaches

Recent advances in visual tracking methods allow following a given object or individual in presence of significant clutter or partial occlusions in a single or a set of overlapping camera views. The question of when person detections in different views or at different time instants can be linked to the same individual is of fundamental importance to the video analysis in large-scale network of ...

Coupled person orientation estimation and appearance modeling using spherical harmonics

Person Reidentification and Recognition in Video

Person recognition has been a challenging research problem for computer vision researchers for many years. A variation of this generic problem is that of identifying the reappearance of the same person in different segments to tag people in a family video. Often we are asked to answer seemingly simple queries such as ‘how many different people are in this video? or ‘find all instances of this p...

Person Re-identification Using Appearance Classification

In this paper, we present a person re-identification method based on appearance classification. It consists a human silhouette comparison by characterizing and classification of a persons appearance (the frontal and the back appearance) using the geometric distance between the detected head of person and the camera. The combination of the head detector, the orthogonal iteration algorithm to hel...

Temporal dynamic appearance modeling for online multi-person tracking

Robust online multi-person tracking requires the correct associations of online detection responses with existing trajectories. We address this problem by developing a novel appearance modeling approach to provide accurate appearance affinities to guide data association. In contrast to most existing algorithms that only consider the spatial structure of human appearances, we exploit the tempora...