Detecting dance motion structure through music analysis
Takaaki Shiratori,Atsushi Nakazawa,Katsushi Ikeuchi +2 more
- 17 May 2004
- pp 857-862
TL;DR: This work introduces musical information for motion structure analysis, which automatically detects the musical rhythm and segmments the original motion, an classifies them as to the primitive motions.
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Abstract: Currently, many important intangible cultural properties of the world are being lost because of the lack of successive performers. Digital archiving technology is one of the effective solutions for this issue, and we have started our digital archiving project of cultural properties including these intangible ones. For these human motion archives, the method of automatic motion structure analysis is vital for a variety of purposes. We believe that the dance motion consists of "primitive motions" and that motion analysis is necessary to detect these components. Particularly for dance motions, we think these primitives must be synchronized to the musical rhythm. In this work, we introduce musical information for motion structure analysis. This method automatically detects the musical rhythm and segmments the original motion, an classifies them as to the primitive motions. The experimental results confirm that our motion analysis yielded the primitive motions in accordance to the musical rhythm.
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Figures
Figure 1: Algorithm Overview 
Figure 11: Segmentation result - Jongara-bushi 
Figure 10: Segmentation result - Aizu-bandaisan dance(male) 
Figure 9: Segmentation result - Aizu-bandaisan dance(female) 
Figure 2: Onset Component Extraction: Calculating how much power increases from ”PrevPow” 
Figure 4: Body Center Coordinate System
Citations
Producing stylized videos using the AnimVideo rendering tool
Rafael Beserra Gomes,Lucas M. Oliveira,Laurindo S. Britto-Neto,Tiago S. Santos,Gilbran S. Andrade,Bruno M. Carvalho,Luiz Marcos Garcia Gonçalves +6 more
TL;DR: The AnimVideo rendering tool that was developed for stylizing videos with temporal coherence is described, which provides the option of initializing the optical flow computation with displacement maps computed by homographies that map objects in adjacent frames.
370
Supervised pattern classification based on optimum-path forest
TL;DR: A general algorithm to learn from errors on an evaluation set without increasing the training set is proposed, and the advantages of the method with respect to SVM, ANN-MLP, and k-NN classifiers are shown in several experiments with datasets of various types.
Dancing-to-Music Character Animation
TL;DR: A new approach for synthesizing dance performance matched to input music, based on the emotional aspects of dance performance, which creates dance performance as if a character was listening and expressively dancing to the music.
166
DeepDance: Music-to-Dance Motion Choreography With Adversarial Learning
TL;DR: A GAN-based cross-modal association framework, DeepDance, which correlates two different modalities (dance motion and music) together, aiming at creating the desired dance sequence in terms of the input music, and is able to create long realistic dance sequences.
139
Humanoid Robot's Autonomous Acquisition of Proto-Symbols through Motion Segmentation
Wataru Takano,Yoshihiko Nakamura +1 more
- 01 Dec 2006
TL;DR: An automatic motion segmentation method utilizing correlation among movements for a short time period is proposed and it is shown that it is possible to acquire proto symbols by providing the automatically segmented motion patterns with the mimesis system.
91
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