@InProceedings{Moll2019c, author = {Philipp Moll and Andreas Leibetseder and Sabrina Kletz and Mathias Lux and Bernd Muenzer}, booktitle = {Proceedings of the 10th {ACM} Multimedia Systems Conference}, title = {{Alternative inputs for games and AR/VR applications}}, year = {2019}, month = {jun}, pages = {320--323}, publisher = {ACM}, abstract = {In multimedia research, scientific progress is often slowed downby high demands on hard- and software. However, hardware con-tinuously improves and today’s hardware got powerful enoughto meet the performance demands of complex 3D and deep learn-ing applications. With this demo, we demonstrate that utilizingdeep learning and 3D modeling is not a major barrier anymorewhen building prototypes for showcasing research projects. Ourweb-based game, called “HeadbangZ”, showcases a novel gesture-based input methodology realized through deeply learned poseestimation and user interaction in a 3D environment. Since gesture-based inputs increase the immersion in virtual environments, weassume this input methodology to be especially useful for AR/VRapplications and games. Furthermore, we demonstrate that rapidprototyping of applications using novel technologies, such as deeplearning, is even possible within 48 hours by developing a workingdemo within this time frame. Finally, we provide insights into whatwe learned during the development of HeadbangZ to encourageother researchers to make use of novel technologies. In referenceto Stephen Harper’s quote “Having hit a wall, the next logical stepis not to bang our heads against it.”, we hope that the presentationof HeadbangZ encourages researchers to bang their heads rhythmi-cally to rock music instead of angrily against a virtual wall createdby hard- and software limitations.}, doi = {10.1145/3304109.3323832}, keywords = {Alternative Inputs, Deep Learning, Rhythm Games}, url = {https://dl.acm.org/citation.cfm?id=3323832} }