Evaluation on the Compactness of Supervoxels
Published in ICIP, 2018
Abstract: Supervoxels are perceptually meaningful atomic spatiotemporal regions in videos, which has great potential to reduce the computational complexity of downstream video applications. Many methods have been proposed for generating supervoxels. To effectively evaluate these methods, a novel supervoxel library and benchmark called LIBSVX with seven collected metrics was recently established. In this paper, we propose a new compactness metric which measures the shape regularity of supervoxels and is served as a necessary complement to the existing metrics. To demonstrate its necessity, we first explore the relations between the new metric and existing ones. Correlation analysis shows that the new metric has a weak correlation with (i.e., nearly independent of) existing metrics, and so reflects a new characteristic of supervoxel quality. Second, we investigate two real-world video applications. Experimental results show that the new metric can effectively predict some important application performance, while most existing metrics cannot do so.
Recommended citation: Ran Yi, Yong-Jin Liu, Yu-Kun Lai. Evaluation on the Compactness of Supervoxels. IEEE International Conference on Image Processing (ICIP 18), pp. 2212-2216, 2018.