Understanding how skilled performance in human endeavor is acquired through practice has benefited markedly from technologies that can track movements of the limb, body and eyes with reference to the environment. A significant challenge within this context is to develop time efficient methods for observing multiple levels of motor system activity throughout practice. Whilst, activity can be recorded using video based systems, crossing multiple levels of analysis is a substantive problematic within the computer vision and human movement domains. The goal of this work is to develop a registration system to collect movement activity in an environment typical to those that individuals normally seek to participate (sports and physical activities). Detailed are the registration system and procedure to collect data necessary for studying skill acquisition processes during difficult indoor climbing tasks, practiced by skilled climbers. Of particular interest are the problems addressed in trajectory reconstruction when faced with limitations of the registration process and equipment in such unconstrained setups. These include: abrupt movements that violate the common assumption of the smoothness of the camera trajectory; significant motion blur and rolling shutter effects; highly repetitive environment consisting of many similar objects.
CITATION STYLE
Schmidt, A., Orth, D., & Seifert, L. (2016). Collection of visual data in climbing experiments for addressing the role of multi-modal exploration in motor learning efficiency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10016 LNCS, pp. 674–684). Springer Verlag. https://doi.org/10.1007/978-3-319-48680-2_59
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