With Thanks

1980

The goal of this project was to perform analysis on human motion capture data and provide useful insight for applications necessitating movement correction. We built a library of tools that could parse .bvh files and then visualize, filter, compress and structure the data so that it can be analyzed with traditional data analysis techniques. Equipped with this custom set of tools, we seeked to demonstrate the application of motion capture to the field of sports analytics. We built several classifiers that could determine the success of a free­throw shot in basketball by making use of input parameters that consisted of key features related to the shooting motion. These tools allowed us to investigate the various attributes that lead to a shot's success and assess their importance based on the individual that performs the shot. The work conducted here serves as a strong base for developing programs that can provide customized coaching feedback for individuals attempting to strength...

Body, Space & Technology, 2020

The following is a review of the 6th International Conference on Motion and Computing at Arizona State University, October 10–12, 2019. The theme of the interdisciplinary conference was Movement Imaginaries and included papers, panels, presentations, performances, demos, and workshops from both scholars and artists from a wide range of disciplines. This review focuses on the panel “Generative tension in cross-disciplinary collaboration”, from John MacCallum, Teoma Naccarato and Jessica Rajko considering the question: “what aspects of your practice/research are invisible to your collaborators?”

From the overall form of the music to the smallest rhythmical facet, each aspect defines how dancers realize the sound and movements. Especially in the field of dance the factors determining this connection can happen within fractions of a second. To understand these events and how musical parameters let dancers recognize music as "danceable", Motion Capture (MoCap) can help by capturing movement in 3D space together with the music. This allows the reconstruction of a performance, which then can be re-related to musical parameters. The paper will elaborate in what ways MoCap technology can support music and dance research, and what kind of problems arise with movement analysis in the special case of tango argentino.

… of the Royal …, 2009

Wearable computing devices and body sensor networks (BSNs) are becoming more prevalent. Collecting the data necessary to develop new concepts for these systems can be difficult. We present the MotionSynthesis Toolset (MoST) to alleviate some of the difficulties in data collection and algorithm development. This toolset allows researchers to generate a sequence of movements (i.e. a diary), synthesize a data stream using real sensor data, visualize, and validate the sequence of movements and data with video and waveforms.

ArXiv, 2015

Human motion analysis and understanding has been, and is still, the focus of attention of many disciplines which is considered an obvious indicator of the wide and massive importance of the subject. The purpose of this article is to shed some light on this very important subject, so it can be a good insight for a novice computer vision researcher in this field by providing him/her with a wealth of knowledge about the subject covering many directions. There are two main contributions of this article. The first one investigates various aspects of some disciplines (e.g., arts, philosophy, psychology, and neuroscience) that are interested in the subject and review some of their contributions stressing on those that can be useful for computer vision researchers. Moreover, many examples are illustrated to indicate the benefits of integrating concepts and results among different disciplines. The second contribution is concerned with the subject from the computer vision aspect where we disc...

Machine Vision and Applications, 2003

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