The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition
Open accessAbstract
This paper describes a novel method called Deep Dynamic Neural Networks (DDNN) for multimodal gesture recognition. A semi-supervised hierarchical dynamic framework based on a Hidden Markov Model (HMM) is proposed for simultaneous gesture segmentation and recognition where skeleton joint information, depth and RGB images, are the multimodal input observations. Unlike most traditional approaches that rely on the construction of complex handcrafted features, our approach learns high-level spatio-temporal representations using deep neural networks suited to the input modality: a Gaussian-Bernouilli Deep Belief Network (DBN) to handle skeletal dynamics, and a 3D Convolutional Neural Network (3DCNN) to manage and fuse batches of depth and RGB images. This is achieved through the modeling and learning of the emission probabilities of the HMM required to infer the gesture sequence. This purely data driven approach achieves a Jaccard index score of 0.81 in the ChaLearn LAP gesture spotting challenge. The performance is on par with a variety of state-of-the-art hand-tuned feature-based approaches and other learning-based methods, therefore opening the door to the use of deep learning techniques in order to further explore multimodal time series data.
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Cited by
Deep multimodal learning: a survey on recent advances and trends
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A Low Power, Fully Event-Based Gesture Recognition System
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A Survey of Model Compression and Acceleration for Deep Neural Networks
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End-to-End Multimodal Emotion Recognition using Deep Neural Networks
Tzirakis, P., Trigeorgis, G., Nicolaou, M. A., Schuller, B., & Zafeiriou, S. (2017) · arXiv · doi:10.48550/arxiv.1704.08619 · Cited by 752
Metadata
- Authors
- Wu, D., Pigou, L., Kindermans, P.-J., Le, N. D.-H., Shao, L., Dambre, J., & Odobez, J.-M.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2016-08-01
- Volume
- 38
- Issue
- 8
- Pages
- 1583-1597
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- 1939-3539
- OpenAlex
- W2295038166
- Cited by
- 453
- References
- 10
- FWCI
- 95.97
- Type
- journal article
- Language
- en
- Open access
- green
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- Wu, D., Pigou, L., Kindermans, P.-J., Le, N. D.-H., Shao, L., Dambre, J., & Odobez, J.-M. (2016). Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2016.2537340
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