Video-based gait analysis of 3D silhouettes

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Musculoskeletal diseases and disorders are one of the leading causes of physician visits in Canada and have a major impact on society in terms of illness, long-term disability and economics. As the Canadian population is aging, these problems will rapidly increase in the future. New biomedical technologies to identify and diagnose early significant abnormalities for more efficient treatment and a faster recovery of the patient are thus needed. For that matter, gait analysis has shown a lot of evidences demonstrating its potential for clinical medical practice. In this context, the general long-term vision of this program of research is to identify relevant parameters from the dynamics of reconstructed 3D body silhouettes for activity recognition. In particular, we will focus during the next years on 3D gait analysis in the clinic and at home.***Different innovative multi-camera approaches and technologies will be investigated for the real-time 3D reconstruction. Then the 3D silhouette motion of normal subjects will be described with a statistical distribution of parameters in a lower-dimensional space using machine learning. For a patient, the identification of significant differences from normality in this low-dimensional space will lead to a "gait quality" index to assess ambulatory problems. Pathological gaits will also be represented similarly for comparison and classification purposes. In all cases, computer-generated animated humans will be added to the training dataset to represent the large range of anthropometric and gait properties of humans and improve learning.***A crucial step is the validation of the approach for both the 3D reconstruction and gait assessment. 3D data precision will be measured with 3D geometric object and human mannequins of known dimensions. Gait analysis will be tested first with computer-generated animated humans and a database of multiple 3D walking humans reconstructed by visual hull extraction. Later on, further experiments will be conducted with student volunteers performing normal and simulated gait impairments in laboratory. Finally, patients will be recruited at University Hospitals for a real clinical assessment. Comparisons with high-end specialized equipment and gold standard functional tests are also planned to determine the ability of our systems to accurately quantify functional ambulatory performance.***In addition to pathological gait analysis, we expect that other applications in healthcare (e.g. balance assessment, body flexion measurements (bending tests), fall and other accident detections, patient monitoring, evaluation in kinesiology/sport etc.) and other areas (e.g. biometry, activity recognition, surveillance, gaming, 3D human-computer interface, robotics etc.) will benefit from this research.**