Unsupervised learning spatio-temporal features for human activity recognition from RGB-D video data
(2013)
Journal Article
Chen, G., Zhang, F., Giuliani, M., Buckl, C., & Knoll, A. (2013). Unsupervised learning spatio-temporal features for human activity recognition from RGB-D video data. Lecture Notes in Artificial Intelligence, 8239 LNAI, 341-350. https://doi.org/10.1007/978-3-319-02675-6_34
Being able to recognize human activities is essential for several applications, including social robotics. The recently developed commodity depth sensors open up newpossibilities of dealingwith this problem. Existing techniques extract hand-tuned fea... Read More about Unsupervised learning spatio-temporal features for human activity recognition from RGB-D video data.