A Multiple Component Matching Framework for Person Re-Identification

Computer Science – Computer Vision and Pattern Recognition

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Accepted paper, 16th Int. Conf. on Image Analysis and Processing (ICIAP 2011), Ravenna, Italy, 14/09/2011

Scientific paper

Person re-identification consists in recognizing an individual that has already been observed over a network of cameras. It is a novel and challenging research topic in computer vision, for which no reference framework exists yet. Despite this, previous works share similar representations of human body based on part decomposition and the implicit concept of multiple instances. Building on these similarities, we propose a Multiple Component Matching (MCM) framework for the person re-identification problem, which is inspired by Multiple Component Learning, a framework recently proposed for object detection. We show that previous techniques for person re-identification can be considered particular implementations of our MCM framework. We then present a novel person re-identification technique as a direct, simple implementation of our framework, focused in particular on robustness to varying lighting conditions, and show that it can attain state of the art performances.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A Multiple Component Matching Framework for Person Re-Identification does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Multiple Component Matching Framework for Person Re-Identification, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Multiple Component Matching Framework for Person Re-Identification will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-497194

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.