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Robust real-time periodic motion detection, analysis, and applications
Abstract
We describe new techniques to detect and analyze periodic motion as seen from both a static and a moving camera. By tracking objects of interest, we compute an object's self-similarity as it evolves in time. For periodic motion, the self-similarity measure is also periodic and we apply time-frequency analysis to detect and characterize the periodic motion. The periodicity is also analyzed robustly using the 2D lattice structures inherent in similarity matrices. A real-time system has been implemented to track and classify objects using periodicity. Examples of object classification (people, running dogs, vehicles), person counting, and nonstationary periodicity are provided.
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Cited by
A survey on vision-based human action recognition
Poppe, R. (2010) · Image and Vision Computing · doi:10.1016/j.imavis.2009.11.014 · Cited by 2,242
A Multi-stream Bi-directional Recurrent Neural Network for Fine-Grained Action Detection
Singh, B., Marks, T. K., Jones, M., Tuzel, O., & Shao, M. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.216 · Cited by 461
Ezzat, M. A., Abd El Ghany, M. A., Almotairi, S., & Salem, M. A.-M. (2021) · Sensors · doi:10.3390/s21093222 · Cited by 39
Learning Periodic Tasks from Human Demonstrations
Yang, J., Zhang, J., Settle, C., Rai, A., Antonova, R., & Bohg, J. (2022) · 2022 International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra46639.2022.9812402 · Cited by 21
A Study on Classification for Static and Moving Object in Video Surveillance System
Uttarakhand Technical University/Computer Science, D., Mishra, P. K., & Saroha, G. P. (2016) · International Journal of Image, Graphics and Signal Processing · doi:10.5815/ijigsp.2016.05.07 · Cited by 17
Nonstandard Periodic Gait Energy Image for Gait Recognition and Data Augmentation
Wang, K., Liu, L., Lee, Y., Ding, X., & Lin, J. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-31723-2_17 · Cited by 12
Metadata
- Authors
- Cutler, R., & Davis, L. S.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2000
- Volume
- 22
- Issue
- 8
- Pages
- 781-796
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2143023146
- Cited by
- 696
- References
- 0
- FWCI
- 22.36
- Type
- journal article
- Language
- en
- Open access
- closed
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