A method for outdoor skateboarding video games

Anlauff, Jan; Weitnauer, Erik; Lehnhardt, Alexander; Schirmer, Stefanie; Zehe, Sebastian; Tonekaboni, Keywan

doi:10.1145/1971630.1971642

Cited by 18 publications

(11 citation statements)

References 7 publications

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“…Electromagnetics Studying correlation between reverberation chamber measurements collected at different stirrer positions (Pirkl et al, 2012) Entertainment Technology Designing a video game controlled by performing tricks on a skateboard (Anlauff et al, 2010).…”

Section: Potential Applicationsmentioning

confidence: 99%

Numerical implementation of the QuEST function

Ledoit

Wolf

2017

Computational Statistics & Data Analysis

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Certain estimation problems involving the covariance matrix in large dimensions are considered. Due to the breakdown of finite-dimensional asymptotic theory when the dimension is not negligible with respect to the sample size, it is necessary to resort to an alternative framework known as large-dimensional asymptotics. Recently, an estimator of the eigenvalues of the population covariance matrix has been proposed that is consistent according to a mean-squared criterion under large-dimensional asymptotics. It requires numerical inversion of a multivariate nonrandom function called the QuEST function. The numerical implementation of this QuEST function in practice is explained through a series of six successive steps. An algorithm is provided in order to compute the Jacobian of the QuEST function analytically, which is necessary for numerical inversion via a nonlinear optimizer. Monte Carlo simulations document the effectiveness of the code.

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Section: Potential Applicationsmentioning

confidence: 99%

Numerical implementation of the QuEST function

Ledoit

Wolf

2017

Computational Statistics & Data Analysis

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“…For example, Tilt n' Roll [1,16] displays visual feedback on a skater's smartphone directly after trick attempts to help learning tricks. This shows us that simple technologies (accelerometers) can be used to capture skateboarding data.…”

Section: Related Workmentioning

confidence: 99%

Designing interactive technology for skateboarding

Pijnappel

Mueller

2014

Proceedings of the 8th International Conference on Tangible, Embedded and Embodied Interaction

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Interactive technology is increasingly used to support physical activities. However, there is limited knowledge about how interactive technology should be designed to support trick-focused experiences such as skateboarding. We developed Copy Paste Skate, a novel multimodal feedback system, and studied its use by 21 avid skateboarders to explore the design of interactive technology for skateboarding. Based on observations and interviews we articulate two key design dimensions that highlight how designing for skateboarding means supporting execution quality of tricks as well as supporting the trick originality. We also present 4 design strategies to help designers support both dimensions in one integrated design. Our work extends designers' knowledge about how to design interactive technology for skateboarding, ultimately extending our understanding of how interactive technology can support people being physically active.

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“…The LDA classifier was modeled through a database composed of 20 tricks collected for each class. The classification method showed a 90% true positive classification, and real-time application was possible in modern smartphones (Anlauff et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…The Tilt 'n' Roll was a prototype game developed by Anlauff et al (2010), whereby a conventional skateboard was equipped with IMU sensors (3D accelerometer and gyroscope) that allowed the accelerations imposed on the skateboard to be monitored, and the differentiation of three tricks; Ollie, Frontside Ollie, and Bail (incorrect attempt/fall). A linear discriminant analysis (LDA) was used for trick classification, with 0.5 s windows to detect events in the IMU signal, sampled at 70 samples/s.…”

Section: Introductionmentioning

confidence: 99%

“…The aforementioned studies used similar methods of data acquisition and detection, and both used linear regression techniques to classify the sample space. Furthermore, both studies pointed to a need for more efficient and faster classification algorithms so that larger groups of tricks can be detectable, especially considering the wide variety of existing techniques used in Street skateboarding (Anlauff et al, 2010;Groh et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Development of a skateboarding trick classifier using accelerometry and machine learning

et al. 2017

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inclusion of the sport of skateboarding in the Tokyo 2020 Olympic Games. The Tokyo 2020 Skateboarding Commission (TSC), together with the IOC, will oversee the insertion and regulation of the sport of skateboarding in the Olympics (Tokyo…, 2016). Modern skateboarding (Street) uses the urban architecture (banks, walls, steps, handrails) as obstacles, with the skateboarder making use of a variety of different types of tricks to overcome the obstacles (Candotti et al., 2012). Research has shown the practice of skateboarding in urban regions to present a greater risk of injuries and accidents (Everett, 2002), where the most affected are children and untrained beginners (Department…, 2013; Fountain and Meyers, 1996; Forsman and Eriksson, 2001). Given the growing popularity of this sport and its intrinsic risk factor, alternative ways to assist the development of this discipline should be pursued, and the use of computerassisted assessment (CAA) may be a promising tool. Exertion Games, also called exergames, are games where the application of physical effort by the user is necessary (Muller et al., 2008). Studies have already proven that interactive simulations can lead to an improvement in sports performance, such as with skating and ice speed skating (Stienstra et al., 2011), rowing (Broker and Crawley, 2001), and even swimming (Marc et al., 2009).

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A method for outdoor skateboarding video games

Cited by 18 publications

References 7 publications

Numerical implementation of the QuEST function

Numerical implementation of the QuEST function

Designing interactive technology for skateboarding

Development of a skateboarding trick classifier using accelerometry and machine learning

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