0000000000514754
AUTHOR
Johel Miteran
showing 5 related works from this author
Definition and performance evaluation of a robust SVM based fall dectection system
2012
International audience
Apprentissage incrémental pour la détection de chute de personnes âgées
2015
International audience; Dans ce papier, nous proposons une méthodologie d'évolution supervisée d'un modèle de classification, spécifique à un système de détection de chute de personnes mis au point précédemment. Cette méthodologie met en oeuvre la méthode de détection, un protocole d'apprentissage incrémental ou évolutif, et une méthode d'évaluation et de comparaison des performances, devant conduire à une amélioration des capacités de détection de chutes sur un système embarqué de type caméra intelligente.
Robust spatio-temporal descriptors for real-time SVM-based fall detection
2014
International audience
Optimised spatio-temporal descriptors for real-time fall detection : comparison of SVM and Adaboost based classification
2013
International audience; We propose a supervised approach to detect falls in home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing to evaluate fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual tr…
Video Scene analysis for a configurable hardware accelerator dedicated to Smart Camera
2012
International audience; According to the Center for Research and Prevention of Injuries report, fall-caused injuries of elderly people in UE- 27 are five times as frequent as other injury causes which reduce considerably their mobility and independence. Among the diverse applications of computer vision systems, object detection and event recognition are of the most prominent related recognition and motion analysis, that is, researchers had the idea to spread it in fall detection. The fall event, extracted automatically from the video scene represents itself, crucial information that can be used to alert emergency. In this context, visual information on the corresponding scene is highly impo…