13 April 2018 A deep learning pipeline for Indian dance style classification
Author Affiliations +
Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 1069611 (2018) https://doi.org/10.1117/12.2309445
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria
Abstract
In this paper, we address the problem of dance style classification to classify Indian dance or any dance in general. We propose a 3-step deep learning pipeline. First, we extract 14 essential joint locations of the dancer from each video frame, this helps us to derive any body region location within the frame, we use this in the second step which forms the main part of our pipeline. Here, we divide the dancer into regions of important motion in each video frame. We then extract patches centered at these regions. Main discriminative motion is captured in these patches. We stack the features from all such patches of a frame into a single vector and form our hierarchical dance pose descriptor. Finally, in the third step, we build a high level representation of the dance video using the hierarchical descriptors and train it using a Recurrent Neural Network (RNN) for classification. Our novelty also lies in the way we use multiple representations for a single video. This helps us to: (1) Overcome the RNN limitation of learning small sequences over big sequences such as dance; (2) Extract more data from the available dataset for effective deep learning by training multiple representations. Our contributions in this paper are three-folds: (1) We provide a deep learning pipeline for classification of any form of dance; (2) We prove that a segmented representation of a dance video works well with sequence learning techniques for recognition purposes; (3) We extend and refine the ICD dataset and provide a new dataset for evaluation of dance. Our model performs comparable or better in some cases than the state-of-the-art on action recognition benchmarks.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Swati Dewan, Shubham Agarwal, Navjyoti Singh, "A deep learning pipeline for Indian dance style classification", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 1069611 (13 April 2018); doi: 10.1117/12.2309445; https://doi.org/10.1117/12.2309445
PROCEEDINGS
9 PAGES


SHARE
Back to Top