En utvärdering av Markerless Motion Capture för amatörer

Sammanfattning: Motion capture(“MoCap”) has been used for a long time in the movie and videogame industries to animate digital characters. This technology commonly requires a studio and expensive stationary equipment. However, in recent years markerless MoCap has emerged. This is a technology that uses machine learning to estimate and reproduce the movements of humans. This technology can be used with a single video camera thus making it more accessible. This study relates to research on motion capture, machine learning and computer animation. The study examines a selection of markerless MoCap tools available on the market with amateurs and small businesses as target audiences. This to explore to which extent markerless MoCap for amateurs is suitable for use. The research questions asked in this study are: How well do these tools recreate motions from an animation? How are these results affected by aggravating circumstances? How do the results of the tools differ from each other? To explore these questions, a selection of five markerless MoCap services was made. These five services were then tested to study their performances in different aggravating circumstances. An original animation was created and used in these tests. The results from these tests were analyzed using a qualitative visual analysis and a numerical analysis of extreme values. The study found the tools could not accurately reproduce the animation they were given to process. The most prominent problem being that of depth perception, which resulted in the processed animations often deviating in depth. The services also had obvious problems with recreating arms. The study also found that some of the different aggravating circumstances affected the results more than others. The results of this study shows that markerless MoCap for amateurs still has development ahead of it before the technology can be considered an effective tool.