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 ID3D-4.7
Paper Title CLUSAC: CLUSTERING SAMPLE CONSENSUS FOR FUNDAMENTAL MATRIX ESTIMATION
Authors Xuanyu Xiao, Zongqing Lu, Tsinghua University, China; Jing-Hao Xue, University College London, United Kingdom
Session3D-4: 3D Image and Video Processing
LocationArea J
Session Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Poster
Topic Three-Dimensional Image and Video Processing: Stereoscopic and multiview processing and display
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract In the process of model fitting for fundamental matrix estimation, RANSAC and its variants disregard and fail to reduce the interference of outliers. These methods select correspondences and calculate the model scores from the original dataset. In this work, we propose an inlier filtering method that can filter inliers from the original dataset. Using the filtered inliers can substantially reduce the interference of outliers. Based on the filtered inliers, we propose a new algorithm called CLUSAC, which calculates model quality scores on all filtered inliers. Our approach is evaluated through estimating the fundamental matrix in the dataset kusvod2, and it shows superior performance to other compared RANSAC variants in terms of precision.