orsel Dans Verilerinin Analizi ve Sentezi Analysis and Synthesis of Multiview Audio-Visual Dance Figures
Ferda Ofli, Y. Demir, Cristian Canton-Ferrer, Joëlle Tilmanne, Elif Bozkurt, Y. Yemez, Engin Erzin, Ahmet Murat Tekalp, Lale Akarun, A. T. Erdem · 2008
This paper presents a framework for audio-driven human body motion analysis and synthesis. The video is analyzed to capture the time-varying posture of the dancer's body whereas the musical audio signal is processed to extract the beat in- formation. The human body posture is extracted from multi- view video information without any human intervention using a novel marker-based algorithm based on annealing particle fil- tering. Body movements of the dancer are characterized by a set of recurring semantic motion patterns, i.e., dance figures. Each dance figure is modeled in a supervised manner with a set of HMM (Hidden Markov Model) structures and the associated beat frequency. In synthesis, given an audio signal of a learned musical type, the motion parameters of the corresponding dance figures are synthesized via the trained HMM structures in syn- chrony with the input audio signal based on the estimated tempo information. Finally, the generated motion parameters are ani- mated along with the musical audio using a graphical animation tool. Experimental results demonstrate the effectiveness of the proposed framework. 1. Giris ¸