Tracking multiple persons under partial and global occlusions: application to customers behavior analysis
| Autor: | Djamal Merad, Rabah Iguernaissi, Pierre Drap, Kheir-Eddine Aziz, Bernard Fertil |
|---|---|
| Přispěvatelé: | Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique et Systèmes (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Images et Modèles (I&M), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Domingues Vinhas, William, Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing 020206 networking & telecommunications Tracking system 02 engineering and technology Tracking (particle physics) [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Artificial Intelligence Video tracking Signal Processing 0202 electrical engineering electronic engineering information engineering Identity (object-oriented programming) 020201 artificial intelligence & image processing Computer vision Segmentation Computer Vision and Pattern Recognition Artificial intelligence Particle filter business Software |
| Zdroj: | Pattern Recognition Letters Pattern Recognition Letters, 2016 Pattern Recognition Letters, Elsevier, 2016 |
| ISSN: | 0167-8655 |
| Popis: | Tracking multiple peoples in mono-camera tracking system.Occlusions management with a re-identification module in multiple peoples tracking system.Crowd management by head detection.People segmentation into front/back and head/torso/legs based on head detection technique.Use of tracking system for customers' behavioral analysis. Multiple objects (targets) tracking plays an important role in computer vision. It is considered as the first step in many artificial intelligence applications that are developed to analyze people behavior for either security or statistical purposes. The most important challenge faced by algorithms designed for multiple objects tracking is the identity switches that occur between tracked objects due to occlusions and interactions between these same objects. This work falls within the scope of video-based behavioral marketing analysis and aims to better understand the purchasing behavior of customers by analyzing their movements in a densely-populated sales area. We propose to use a re-identification strategy to prevent these identity switches. This re-identification strategy is based on segmenting detected individuals into head, torso, and legs in addition to the classification of their appearances into front and back poses. This re-identification module is integrated within our tracking system to fuse tracklets obtained from a particle filter based tracking framework in a mono-camera tracking system. The combination of these tracking and re-identification modules allows the recovery of global trajectories for tracked individuals. |
| Databáze: | OpenAIRE |
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