2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDTEC-5.4
Paper Title SEMASUPERPIXEL: A MULTI-CHANNEL PROBABILITY-DRIVEN SUPERPIXEL SEGMENTATION METHOD
Authors Xuehui Wang, Sun Yat-sen University and Shanghai Jiao Tong University, China; Qingyun Zhao, Sun Yat-sen University, China; Lei Fan, Northwestern University, China; Yuzhi Zhao, City University of Hong Kong, China; Tiantian Wang, Qiong Yan, SenseTime Research, China; Long Chen, Sun Yat-sen University, China
SessionTEC-5: Image and Video Processing 1
LocationArea G
Session Time:Monday, 20 September, 13:30 - 15:00
Presentation Time:Monday, 20 September, 13:30 - 15:00
Presentation Poster
Topic Image and Video Processing: Formation and reconstruction
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Superpixel, an efficient image segmentation approach, aggregates a group of similar pixels into the same cluster. Existing superpixel algorithms still mainly focus on the color information while ignoring the semantic distribution knowledge. In this paper, we propose a semantic information-driven method that adopts multi-channel semantic probabilities for superpixel segmentation. By conducting statistical analysis on the semantic output and then formulating the distance measure, the prior knowledge of the semantic with a dynamic confidence value could be utilized by our method during the global update effectively. Extensive experimental evaluations show that our method achieves a leading segmentation quality and convergence speed, compared to other five state-of-the-art algorithms, as measured by boundary recall, undersegmentation error, and explained variation.