| A. Papadakis, E. Mathe, E. Spyrou, Ph. Mylonas |
| A Geometric Approach for Cross-View Human Action Recognition using Deep Learning |
| 11th International Symposium on Image and Signal Processing and Analysis (ISPA 2019), 23-25 September 2019, Dubrovnik, Croatia |
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ABSTRACT
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| In this paper we present an approach for the recognition of human actions which is based on a deep Convolutional Neural Network architecture. More specifically, 3D skeletal joint information is used to create 2D (image) representations. To compensate for potential viewpoint changes, these images are pre-processed using geometric transformations. Then, they are transformed to the spectral domain using well-known transforms. We focus on actions that are close to activities of daily living (ADLs), yet we evaluate our approach using a large-scale action dataset. We cover single-view, cross-view and cross subject cases and thoroughly discuss experimental results and the potential of our approach.
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| 23 September, 2019 |
| A. Papadakis, E. Mathe, E. Spyrou, Ph. Mylonas, "A Geometric Approach for Cross-View Human Action Recognition using Deep Learning", 11th International Symposium on Image and Signal Processing and Analysis (ISPA 2019), 23-25 September 2019, Dubrovnik, Croatia |
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