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-4.6
Paper Title A REGION-BASED DESCRIPTOR NETWORK FOR UNIFORMLY SAMPLED KEYPOINTS
Authors Kai Lv, Zongqing Lu, Qingmin Liao, Tsinghua University, China
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 Matching keypoint pairs of different images is a basic task of computer vision. Most methods require customized extremum point schemes to obtain the coordinates of feature points with high confidence, which often need complex algorithmic design or a network with higher training difficulty and also ignore the possibility that flat regions can be used as candidate regions of matching points. In this paper, we design a region-based descriptor by combining the context features of a deep network. The new descriptor can give a robust representation of a point even in flat regions. By the new descriptor, we can obtain more high confidence matching points without extremum operation. The experimental results show that our proposed method achieves a performance comparable to state-of-the-art.