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Section: New Results
Introduction
This year Stars has proposed new algorithms related to its three main research axes : perception for activity recognition, semantic activity recognition and software engineering for activity recognition.
Perception for Activity Recognition
Participants : Julien Badie, Slawomir Bak, Vasanth Bathrinarayanan, Piotr Bilinski, Bernard Boulay, François Brémond, Sorana Capalnean, Guillaume Charpiat, Duc Phu Chau, Etienne Corvée, Eben Freeman, Carolina Garate, Jihed Joober, Vaibhav Katiyar, Ratnesh Kumar, Srinidhi Mukanahallipatna, Sabine Moisan, Silviu Serban, Malik Souded, Anh Tuan Nghiem, Monique Thonnat, Sofia Zaidenberg.
This year Stars has extended an efficient algorithm for detecting people. We have also proposed a new algorithm for re-identification of people through a camera network. We have realized a new algorithm for the recognition of short actions and validated also its performance on several benchmarking databases (e.g. ADL). We have improved a generic event recognition algorithm by handling event uncertainty at several processing levels. More precisely, the new results for perception for activity recognition concern:
Image Compression and Modelization ( 6.2 )
Background Subtraction ( 6.3 )
Fiber Based Video Segmentation ( 6.4 )
Enforcement of Monotonous Shape Growth/Shrinkage in Video Segmentation ( 6.5 )
Dynamic and Robust Object Tracking in a Single Camera View ( 6.6 )
Optimized Cascade of Classifiers for People Detection Using Covariance Features ( 6.7 )
Learning to Match Appearances by Correlations in a Covariance Metric Space ( 6.8 )
Recovering Tracking Errors with Human Re-identification ( 6.9 )
Human Action Recognition in Videos ( 6.10 )
Group Interaction and Group Tracking for Video-surveillance in Underground Railway Stations ( 6.11 )
Crowd Event Monitoring Using Texture and Motion Analysis ( 6.12 )
Detecting Falling People ( 6.13 )
People Detection Framework ( 6.14 )
Semantic Activity Recognition
Participants : Sorana Capalnean, Guillaume Charpiat, Cintia Corti, Carlos -Fernando Crispim Junior, Hervé Falciani, Baptiste Fosty, Qioa Ma, Firat Ozemir, Jose-Luis Patino Vilchis, Guido-Tomas Pusiol, Rim Romdhame, Bertrand Simon, Abhineshwar Tomar.
Concerning semantic activity recognition, the contributions are :
A Model-based Framework for Activity Recognition of Older People using Multiple sensors ( 6.15 )
Activity Recognition for Older People using Kinect ( 6.16 )
Descriptors of Depth-Camera Videos for Alzheimer Symptom Detection ( 6.17 )
Online Activity Learning from Subway Surveillance Videos ( 6.18 )
Automatic Activity Detection Modeling and Recognition: ADMR ( 6.19 )
Software Engineering for Activity Recognition
Participants : François Brémond, Daniel Gaffé, Julien Gueytat, Baptiste Fosty, Sabine Moisan, Anh tuan Nghiem, Annie Ressouche, Jean-Paul Rigault, Leonardo Rocha, Luis-Emiliano Sanchez, Swaminathan Sankaranarayanan.
This year Stars has continued the development of the SUP platform. This latter is the backbone of the team experiments to implement the new algorithms. We continue to improve our meta-modelling approach to support the development of video surveillance applications based on SUP. This year we have focused on an architecture for run time adaptation and on metrics to drive dynamic architecture changes. We continue the development of a scenario analysis module (SAM) relying on formal methods to support activity recognition in SUP platform. We improve the theoretical foundations of clem toolkit and we rely on it to build SAM. Finally, we are improving the way we perform adaptation in the definition of a multiple services for device adaptive platform for scenario recognition.
The contributions for this research axis are: