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Unsupervised Online Video Object Segmentation with Motion Property Understanding
Unsupervised Online Video Object Segmentation with Motion Property Understanding
Tao Zhuo, Zhiyong Cheng, Peng Zhang, Yongkang Wong, and Mohan Kankanhalli
Results on DAVIS-2016 TrainVal Dataset (50 videos)
| Measure | NLC | LMP | FSEG | ARP | UOVOS |
|---|---|---|---|---|---|
| J Mean | 64.1 | 69.7 | 71.6 | 76.3 | 77.8 |
| J Recall | 73.1 | 82.9 | 87.7 | 89.2 | 93.6 |
| J Decay | 8.6 | 5.6 | 1.7 | 3.6 | 2.1 |
| F Mean | 59.3 | 66.3 | 65.8 | 71.1 | 72.0 |
| F Recall | 65.8 | 78.3 | 79.0 | 82.8 | 87.7 |
| F Decay | 8.6 | 6.7 | 4.3 | 7.3 | 3.8 |
| T | 36.6 | 68.8 | 29.5 | 35.9 | 33.0 |
NLC: Video Segmentation by Non-Local Consensus voting. A. Faktor, M. Irani, BMVC 2014.
LMP: Learning Motion Patterns in Videos. P. Tokmakov, K. Alahari, C. Schmid, CVPR 2017.
FSEG: FusionSeg: Learning to combine motion and appearance for fully automatic segmentation of generic objects in videos. S. Jain, B. Xiong, K. Grauman, CVPR 2017.
ARP: Primary Object Segmentation in Videos Based on Region Augmentation and Reduction. Y.J. Koh, C.-S. Kim, CVPR 2017.
Setup
Ubuntu
Matlab
Python2.7
Opencv_3.4
Mask-RCNN https://github.com/matterport/Mask_RCNN
Citation
If you use this code, please cite the following paper:
@article{zhuo2018unsupervised, title={Unsupervised Online Video Object Segmentation with Motion Property Understanding}, author={Zhuo, Tao and Cheng, Zhiyong and Zhang, Peng and Wong, Yongkang and Kankanhalli, Mohan}, journal={IEEE Transaction on Image Processing}, year={2019} }
Contact
Tao Zhuo ([email protected])
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