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Gait Analysis, Modelling, and Comparison from Unconstrained Walks and Viewpoints

Project type: PhD Research Project
Duration: May 2005 - May 2012
Institution: Université Laval, Quebec City, Québec, Canada
Group: Computer Vision and Systems Laboratory (CVSL)
Collaborators: Dr Robert Bergevin (PhD adviser), Dept. of Electrical and Computer Engineering, Université Laval
Dr Alexandra B. Albu (PhD co-adviser), Dept. of Electrical and Computer Engineering, University of Victoria

Motivation

Gait analysis, modelling and comparison using computer vision algorithms has recently attracted much attention for medical and surveillance applications. Analyzing and modelling a person's gait with computer vision algorithms has indeed some interesting advantages over more traditional biometrics. For instance, gait can be analyzed and modelled at a distance by observing the person with a camera, which means that no markers or sensors have to be worn by the person. Moreover, gait analysis and modelling using computer vision algorithms does not require the cooperation of the observed people, which thus allows for using gait as a biometric in surveillance applications.

Current gait analysis and modelling approaches have however severe limitations. For instance, several approaches require a side view of the walks since this viewpoint is optimal for gait analysis and modelling. Most approaches also require the walks to be observed far enough from the camera in order to avoid perspective distortion effects that would badly affect the resulting gait analyses and models. Moreover, current approaches do not allow for changes in walk direction and in walking speed, which greatly constraints the walks that can be analyzed and modelled in medical and surveillance applications.

Approach

The approach I proposed in my thesis aims at performing gait analysis, modelling and comparison from unconstrained walks and viewpoints in medical and surveillance applications. The proposed approach mainly consists in a novel view-rectification method that generates a fronto-parallel viewpoint (side view) of the imaged trajectories of body parts. The view-rectification method is based on a novel walk model that uses projective geometry to provide the spatio-temporal links between the body-part positions in the scene and their corresponding positions in the images. The head and the feet are the only body parts that are relevant for the proposed approach. They are automatically localized and tracked in monocular video sequences using a novel body parts tracking algorithm. Gait analysis is performed by a novel method that extracts standard gait measurements from the view-rectified body-part trajectories. A novel gait model based on body-part trajectories is also proposed in order to perform gait modelling and comparison using the dynamics of the gait.

Video

The following video presents the steps of the view-rectification method, which is one of the main contributions of my PhD thesis.

View-rectification of Body-part Trajectories from Monocular Video Sequences


Related Publications

My PhD thesis can be downloaded in PDF format: PhD Thesis PDF. The most important publications related to my PhD project are listed below. For a complete list of my publications, see the publications page.

Frédéric Jean, "Gait Analysis, Modelling, and Comparison from Unconstrained Walks and Viewpoints : View-rectification of Body-part Trajectories from Monocular Video Sequences", PhD Thesis, Université Laval. Quebec City, QC, Canada. April 2012. http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bRWtHOExfbTUza0U http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bZzJ4RFFqcDZJcDA http://www.theses.ulaval.ca/2012/28981/
Frédéric Jean, Robert Bergevin, and Alexandra Branzan-Albu, "Human gait characteristics from unconstrained walks and viewpoints", In Proceedings of the International Conference on Computer Vision Workshops, (Barcelona, Spain), pp. 1883-1888, November 6-13 2011. http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bQ01zcEY2YTFtVE0 http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bYWtKUGRlY0xPRjA
Frédéric Jean, Alexandra Branzan-Albu and Robert Bergevin, "Towards View-Invariant Gait Modeling: Computing View-Normalized Body Part Trajectories", Pattern Recognition, vol. 42, no 11, pp. 2936-2949, November 2009. http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bb2VZNnNPdElPWDA http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bdENQa2Ixc1N1Qm8
Frédéric Jean, Robert Bergevin and Alexandra Branzan-Albu, "Computing and Evaluating View-normalized Body Part Trajectories", Image and Vision Computing, vol. 27, no 9, pp. 1272–1284, August 2009. http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4ba3NOM3FRVEdZcjA http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bMGpiRHo2QlVhWGc
Frédéric Jean, Robert Bergevin and Alexandra Branzan-Albu, "Trajectories Normalization for Viewpoint Invariant Gait Recognition", In Proceedings of the 19th International Conference on Pattern Recognition (ICPR), (Tampa, Florida, USA), December 8-11 2008. http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bdVQzV09kZHF0VEU http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bcEROdjYzd2s5aGM
Frédéric Jean, Robert Bergevin and Alexandra Branzan-Albu, "Computing View-normalized Body Parts Trajectories", In Proceedings of the Fourth IEEE Canadian Conference on Computer and Robot Vision, (Montreal, QC, Canada), pp. 89-96, May 27-30 2007. http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bWDlzSUVtUHNXdlk http://docs.google.com/uc?export=download&id=0B3TPx0P_KI4bV0E0VS0zSklYamc