A fast 3D object recognition algorithm using plane-constrained point pair features

The point pair feature (PPF) algorithm is one of the best-performing 3D object recognition algorithms. However, the high dimensionality of its search space is a disadvantage of this algorithm. This high dimensionality means the feature matching process contains a large number of uninformative featur...

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Vydáno v:Multimedia tools and applications Ročník 79; číslo 39-40; s. 29305 - 29325
Hlavní autoři: Xiao, Zhengtao, Gao, Jian, Wu, Dongqing, Zhang, Lanyu, Chen, Xin
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.10.2020
Témata:
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Multimedia Information Systems
Special Purpose and Application-Based Systems
Feature descriptor
Feature matching
Convex hull
3D object recognition
Point pair features
ISSN:1380-7501, 1573-7721
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Popis
Shrnutí:The point pair feature (PPF) algorithm is one of the best-performing 3D object recognition algorithms. However, the high dimensionality of its search space is a disadvantage of this algorithm. This high dimensionality means the feature matching process contains a large number of uninformative features, which reduces recognition speed. To solve this problem and improve the object recognition speed, this paper proposes a fast 3D object recognition algorithm based on the plane-constrained point pair features. By utilizing the property of the coplanar point pair features and the characteristics of the object placement plane, the proposed algorithm extracts the object placement plane through convex hull area calculation, eliminates irrelevant point pair features, and then performs object recognition with the reduced point pair feature descriptors for the feature matching. Experimental results demonstrate that the proposed algorithm significantly reduces the number of feature descriptors and accelerates the recognition speed of 3D objects in a complex background. Compared to the original point pair feature algorithm, the proposed method can achieve better performance and efficiency for 3D object recognition.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-020-09525-x