Adaptive Neuro-Fuzzy Controller for Multi-Object Tracker
- Others:
- Spatio-Temporal Activity Recognition Systems (STARS) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- School of Computer Engineering [Singapore] (NTU) ; Nanyang Technological University [Singapour]
- Cognition Behaviour Technology (CobTek) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre Hospitalier Universitaire de Nice (CHU Nice)-Institut Claude Pompidou [Nice] (ICP - Nice)-Université Côte d'Azur (UCA)
- ANR-13-SECU-0005,MOVEMENT,Suivi de personnel et vérification biométrique automatiques pour le management sans contrainte des zones de sûreté aéroportuaires(2013)
- European Project: 296104,EC:FP7:SP1-JTI,ENIAC-2011-1,PANORAMA(2012)
- European Project: 324359,EC:FP7:PEOPLE,FP7-PEOPLE-2012-IAPP,CENTAUR(2013)
Description
Sensitivity to scene such as contrast and illumination intensity, is one of the factors significantly affecting the performance of object trackers. In order to overcome this issue, tracker parameters need to be adapted based on changes in contextual information. In this paper, we propose an intelligent mechanism to adapt the tracker parameters, in a real-time and online fashion. When a frame is processed by the tracker, a controller extracts the contextual information, based on which it adapts the tracker parameters for successive frames. The proposed controller relies on a learned neuro-fuzzy inference system to find satisfactory tracker parameter values. The proposed approach is trained on nine publicly available benchmark video data sets and tested on three unrelated video data sets. The performance comparison indicates clear tracking performance improvement in comparison to tracker with static parameter values, as well as other state-of-the art trackers.
Abstract
International audience
Additional details
- URL
- https://hal.inria.fr/hal-01164734
- URN
- urn:oai:HAL:hal-01164734v1
- Origin repository
- UNICA