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

Daniel Leightley dleightley at ieee.org
Fri Aug 4 10:21:05 -05 2017

*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
(12) “In-the-wild” encoding and measuring kinematic signals;
(13) Micro-non-mico facial analysis.


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

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