NDLI: Scale, Rotation and Pose Invariant 3D Object Detection using Log-polar Transform and Singular Value Decomposition

Content Provider	IEEE Xplore Digital Library
Author	Ren xianyi Dan tangren Ding tianhuai Liu yan Zhang wei Zhang Guilin Zhang tianxu
Copyright Year	2006
Description	Author affiliation: Tsinghua Univ., Beijing (Ren xianyi; Dan tangren; Ding tianhuai; Liu yan)
Abstract	This paper proposed a novel biologically motivated 3D object detection algorithm which works robustly in the presence of large scale changes, rotation, occlusion, and pose changes. The robustness to scale and rotation is achieved through log-polar transformation procedure. Singular value decomposition (SVD) in conjunction with the distance-to-feature space measure is used to handle the pose variations and reduce the computational complexity. The system was evaluated using 3D object with varying scale and pose on different complex backgrounds. The experimental results show that the object detector was quite robust to all these variations
Sponsorship	IEEE Circuits and Syst. Soc. HKUST UESTC City Univ. of Hong Kong
Starting Page	480
Ending Page	484
File Size	4972328
Page Count	5
File Format	PDF
ISBN	0780395840
DOI	10.1109/ICCCAS.2006.284681
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image recognition Layout Object detection Detectors Feature extraction Robustness Large-scale systems Artificial intelligence Computational complexity Singular value decomposition
Content Type	Text
Resource Type	Article

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