Robust multi-planar region detection for image mosaic based on hierarchical clustering mechanism

Abstract

Planar structures exist widely in the images of various scenes, and the detection of planar regions is important in many applications related to computer vision, such as image mosaic and three-dimensional reconstruction. In this paper, a robust detection method for multi-planar regions is proposed. After the feature point pairs are extracted, their preference vectors are generated in similar conceptual space. By introducing the shared nearest neighbour in clustering procedure, the feature point pairs with smaller Jaccard distance and more shared nearest neighbours simultaneously are clustered into the same planar region. Because the relationship between the feature point pairs is considered, the accuracy of the inlier probability is high. Our method can detect multi-planar regions correctly without pre-determining the number of regions, and the corresponding clustered feature point pairs can be easily utilised for image mosaic. The experimental results show the effectiveness of the proposed method.

Keywords:

• planar detection
• hierarchical clustering
• image mosaic
• feature points

This work was supported by the Natural Science Foundation of China (60832003 and 60772124), the Natural Science Foundation of Shanghai (11ZR1413400) and the Shanghai Leading Academic Discipline Project, STCSM (S30108 and 08DZ2231100).