Evaluating how different video features influence the visual quality of resultant motiongrams

Motiongrams are visual representations of human motion, generated from regular video recordings. This paper evaluates how different video features may influence the generated motiongram: inversion, colour, filtering, background, lighting, clothing, video size and compression. It is argued that the proposed motiongram implementation is capable of visualising the main motion features even with quite drastic changes in all of the above mentioned variables. Proceedings of the 9th Sound and Music Computing Conference, Copenhagen, Denmark, 11-14 July, 201