Emotion Control of Unstructured Dance Movements
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Supplementary Materials: It is difficult to fully
represent by-products of our results, and appreciate the quality of modified
dance motions in the paper. Therefore, in these pages we include larger
format versions of the intermediate results in the paper, together with more
dance editing results, as well as our user study analysis. Furthermore, we
present the results of the Yumer and Mitra [2016] method. We recommend using the latest
version of Firefox, Chrome, and IE to view these results. 1. Clustering Results:
We
use the hierarchical clustering algorithm to group similar poses into clusters, resulting in five
clusters (crouching, jumping and three different standing styles). Here we
show 100 randomly selected exemplar poses for each cluster. Cluster 1 (standing poses) , Cluster 2 (crouching poses) , Cluster 3 (standing poses) , Cluster 4 (jumping poses) , Cluster 5 (standing poses)
5.
User Study: Representative screen shots for each section of our user study.
Survey 1 Section 1: Emotion Recognition Section 2: Emotion Modification
Survey 2 6.
Comparison with Yumer and Mitra [2016]: The most closely related prior work that transfers styles on
independent actions and can be used for comparison is Yumer
and Mitra [2016]. The authors kindly helped in the
evaluation procedure, running our heterogeneous dance motion data in their
system. However, since our dance motions are highly non-regular and
arbitrary, and since their system is trained using motions of different
nature (locomotion), the produced stylized motions suffer from abnormal
movements and foot-skating. Yumer
and Mitra [2016] method is limited to transfer
style only to those emotions that are in the training dataset, thus style was
transferred only to Angry and Depressed (Sad) emotions. References YUMER,
M. E., AND MITRA, N. J. 2016. Spectral style transfer for human motion
between independent actions. ACM Trans. Graph. 35 (Aug.). |
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