J
Jacqueline Rousseau
Researcher at Université de Montréal
Publications - 69
Citations - 2639
Jacqueline Rousseau is an academic researcher from Université de Montréal. The author has contributed to research in topics: Population & Poison control. The author has an hindex of 19, co-authored 62 publications receiving 2321 citations. Previous affiliations of Jacqueline Rousseau include Queen Mary University of London.
Papers
More filters
Journal ArticleDOI
Robust Video Surveillance for Fall Detection Based on Human Shape Deformation
TL;DR: A new method is proposed to detect falls by analyzing human shape deformation during a video sequence, which gives very good results (as low as 0% error with a multi-camera setup) compared with other common image processing methods.
Proceedings ArticleDOI
Fall Detection from Human Shape and Motion History Using Video Surveillance
TL;DR: A new method to detect falls, which are one of the greatest risk for seniors living alone, is proposed, based on a combination of motion history and human shape variation.
Journal ArticleDOI
Fall Detection With Multiple Cameras: An Occlusion-Resistant Method Based on 3-D Silhouette Vertical Distribution
TL;DR: A new method to detect falls at home, based on a multiple-cameras network for reconstructing the 3-D shape of people, which achieved 99.7% sensitivity and specificity or better with four cameras or more.
Proceedings ArticleDOI
Monocular 3D head tracking to detect falls of elderly people.
TL;DR: This work presents a new method to detect falls using a single camera based on the 3D trajectory of the head, which allows to distinguish falls from normal activities using 3D velocities.
Book ChapterDOI
Fall detection from depth map video sequences
TL;DR: An occlusion robust method is presented based on two features: human centroid height relative to the ground and body velocity, which is an efficient solution to detect falls as the vast majority of falls ends on the ground or near the ground.