[visionlist] CfP: Face and Gesture 2018: Kinect-based Kinematic Data Analysis and Evaluation for Clinical Applications

Face and Gesture 2018 will be holding a special session entitled: Kinect-based Kinematic Data Analysis and Evaluation for Clinical 

In recent years, there has been an increased interest in automated methods for detection, analysis and quantification of human motion (e.g. physical activity, performance execution and rehabilitation). This is due to the increased availability of low-cost multi-modality RGBD marker-less capturing devices. These devices are clinically important to allow for assessment in home-based and remote settings by extracting kinematic features for use in post-stroke recovery, fall prevention, and in-house elderly monitoring. We welcome submissions on the topics related to clinical application of RBGD, including 

(1) Geometric approaches for human motion analysis; (2) Mathematical models for fall prevention and fall detection; (3) Balance performance analysis; (4) Normal and pathological Gait analysis; (5) Postural abnormalities; (6) Moving body symmetry analysis; (7) Elderly coaching and monitoring; (8) Post-stroke rehabilitation using RBD; (9) Evaluation of Kinect-like sensors in kinematic data analysis; (10) Face recognition and analysis for clinical application; (11) Encoding musculoskeletal measurements from depth and/or motion capture data; (12) “In-the-wild” encoding and measuring kinematic signals; (13) Micro-non-mico facial analysis.Organizers: 

Dr. Daniel Leightley, King’s College London, UK (point of contact: daniel.leightley@kcl.ac.uk)Dr. Boulbaba Ben Amor, IMT Lille Douai/CRIStAL CNRS 9189, FranceDr. Moi Hoon Yap, Manchester Metropolitan University, UKDr. Pavan Turaga, Arizona State University, USADr. Anuj Srivastava, Florida State University

You can find more information about this session via http://www.fg2018.org/


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