A generic framework for video understanding applied to group behavior recognition

This paper presents an approach to detect and track groups of people in video-surveillance applications, and to automatically recognize their behavior. This method keeps track of individuals moving together by maintaining a spacial and temporal group coherence. First, people are individually detected and tracked. Second, their trajectories are analyzed over a temporal window and clustered using the Mean-Shift algorithm. A coherence value describes how well a set of people can be described as a group. Furthermore, we propose a formal event description language. The group events recognition approach is successfully validated on 4 camera views from 3 datasets: an airport, a subway, a shopping center corridor and an entrance hall.Comment: (20/03/2012

Le paysage viticole de Sancerre : entre reconnaissance et valorisation

Cet article propose une démarche à la lecture paysagère. Il commence d’abord par la définition complexe du paysage et une méthode de lecture. De ces deux principes épistémologiques découlent la découverte et l’analyse du paysage viticole de Sancerre selon des cheminements et des points de vue situés idéalement en des lieux où un vaste panorama s’offre au regard. Son histoire peut être approfondie à l’aide de cartes postales anciennes et de l’analyse du cadastre sur des périodes variant de cent à deux cents ans. La mise en valeur des paysages en périphérie et au cœur de la ville de Sancerre est une opération de touristification visant l’optimisation de l’attractivité œnotouristique.This article presents an approach for interpreting landscapes. It starts with a complex definition of the landscape and then presents a method of interpretation. The result obtained from these two epistemological principles is the discovery and the analysis of the viticultural landscape of Sancerre via itineraries and points of view ideally situated offering vast panoramic perspectives. The landscape’s historical background may be explored in depth by means of old post cards and the land registry records from periods ranging between one hundred and two hundred years ago. The promotion of these landscapes in the periphery and in the centre of the city of Sancerre is part of an operation for the development of tourism aimed at optimising the wine tourism appeal of the region

Human Posture Recognition in Video Sequence

International audienceThis paper presents a new approach to recognize human postures in video sequences comparing two methods. We first describe these two methods based on 2D appearances. The first one uses projections of moving pixels on the reference axis. The second method decomposes the human silhouette into blocks and learns 2D posture appearances through PCA. Then we use 3D model of posture to make the previous methods independent of the camera position. At the end we give some preliminary results and conclude on the effectiveness of this approach

Posture Recognition with a 3D Human Model

International audienceThis paper proposes an approach to recognise human postures in video sequences, which combines a 2D approach with a 3D human model. The 2D approach consists in projections of moving pixels on the reference axis. The 3D model is a realistic articulated human model which is used to obtain reference postures to compare with test postures. We are interested in a set of specific postures which are representative of typical applications in video interpretation. We give results for recognition of general (e.g. standing) and detailed (e.g standing with one arm up) postures. First results show the effectiveness of our approach for recognition of human posture

Applying 3D Human Model in a Posture Recognition System

International audienceThis paper proposes an approach to recognise human postures in videosequences, which combines a 2D approach with a 3D human model. The 3D model is a realistic articulated human model which is used to obtain reference postures to compare with test postures. Several 2D approaches using different silhouette representations are compared with each other: projections of moving pixels on the reference axis, Hu moments and skeletonisation. We are interested in a set of specific postures which are representative of typical video understanding applications. We describe results for recognition of general postures (e.g. standing) and detailed postures (e.g standing with one arm up) in ambiguous/optimal viewpoint with good/bad segmented silhouette to show the effectiveness of our approach

Improving Person Re-identification by Viewpoint Cues

International audienceRe-identifying people in a network of cameras requires an invariant human representation. State of the art algorithms are likely to fail in real-world scenarios due to serious perspective changes. Most of existing approaches focus on invariant and discriminative features, while ignoring the body alignment issue. In this paper we propose 3 methods for improving the performance of person re-identification. We focus on eliminating perspective distortions by using 3D scene information. Perspective changes are minimized by affine transformations of cropped images containing the target (1). Further we estimate the human pose for (2) clustering data from a video stream and (3) weighting image features. The pose is estimated using 3D scene information and motion of the target. We validated our approach on a publicly available dataset with a network of 8 cameras. The results demonstrated significant increase in the re-identification performance over the state of the art

Monitoring Activities of Daily Living (ADLs) of Elderly Based on 3D Key Human Postures

International audienceThis paper presents a cognitive vision approach to recognize a set of interesting activities of daily living (ADLs) for elderly at home. The proposed approach is composed of a video analysis component and an activity recognition component. A video analysis component contains person detection, person tracking and human posture recognition. A human posture recognition is composed of a set of postures models and a dedicated human posture recognition algorithm. Activity recognition component contains a set of video event models and a dedicated video event recognition algorithm. In this study, we collaborate with medical experts (gerontologists from Nice hospital) to define and model a set of scenarios related to the interesting activities of elderly. In our approach, we propose ten 3D key human postures usefull to recognize a set of interesting human activities regardless of the environment. The novelty of our approach is the proposed 3D key postures and the set of activity models of elderly person living alone in her/his own home. To validate our proposed models, we have performed a set of experiments in the Gerhome laboratory which is a realistic site reproducing the environment of a typical apartment. For these experiments, we have acquired and processed ten video sequences with one actor. The duration of each video sequence is about ten minute

Formylpeptide receptors (version 2019.4) in the IUPHAR/BPS Guide to Pharmacology Database

The formylpeptide receptors (nomenclature agreed by the NC-IUPHAR Subcommittee on the formylpeptide receptor family [185]) respond to exogenous ligands such as the bacterial product fMet-Leu-Phe (fMLP) and endogenous ligands such as annexin I , cathepsin G, amyloid β42, serum amyloid A and spinorphin, derived from β-haemoglobin

Formylpeptide receptors in GtoPdb v.2021.2

The formylpeptide receptors (nomenclature agreed by the NC-IUPHAR Subcommittee on the formylpeptide receptor family [196]) respond to exogenous ligands such as the bacterial product fMet-Leu-Phe (fMLP) and endogenous ligands such as lipoxin A4 (LXA4), 15-epi-lipoxin A4, annexin I , cathepsin G, amyloid β42, serum amyloid A and spinorphin, derived from β-haemoglobin. FPR1 also serves as a plague receptor for selective destruction of human immune cells by Y. pestis [135]. The FPR1/2 agonists 'compound 17b' and 'compound 43' have shown cardiac protective functions [149, 64]