Fast 3D Object Alignment from Depth Image with 3D Fourier Moment Matching on GPU

In this paper, we develop a fast and accurate 3D object alignment system which can be applied to detect objects and estimate their 3D pose from a depth image containing cluttered background. The proposed 3D alignment system consists of two main algorithms: the first is the 3D detection algorithm to detect the top-level object from a depth map of the cluttered 3D objects, and the second is the 3D Fourier based point-set alignment algorithm to estimate the 3D object pose from an input depth image. We also implement the proposed 3D alignment algorithm on a GPU computing platform to speed up the computation of the object detection and Fourier-based image alignment algorithms in order to align the 3D object in real time.

[1]  Shang-Hong Lai,et al.  Robust Fourier-Based Image Alignment with Gradient Complex Image , 2010, 2010 20th International Conference on Pattern Recognition.

[2]  Shang-Hong Lai,et al.  CT-MR Image Registration in 3D K-Space Based on Fourier Moment Matching , 2011, PSIVT.

[3]  George Wolberg,et al.  Image registration using log-polar mappings for recovery of large-scale similarity and projective transformations , 2005, IEEE Transactions on Image Processing.

[4]  Roberto Cipolla,et al.  A Performance Evaluation of Volumetric 3D Interest Point Detectors , 2013, International Journal of Computer Vision.

[5]  Mohammed Bennamoun,et al.  Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Nassir Navab,et al.  Distance transform templates for object detection and pose estimation , 2009, CVPR.

[7]  Shang-Hong Lai,et al.  Fast image alignment with Fourier moment matching on GPU , 2013, 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference.

[8]  Wei Pan,et al.  An Adaptable-Multilayer Fractional Fourier Transform Approach for Image Registration , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Wolfram Burgard,et al.  Point feature extraction on 3D range scans taking into account object boundaries , 2011, 2011 IEEE International Conference on Robotics and Automation.

[10]  C. Steger.  OCCLUSION , CLUTTER , AND ILLUMINATION INVARIANT OBJECT RECOGNITION , 2002 .

[11]  Ray Jarvis,et al.  3D free-form surface registration and object recognition , 2004, International Journal of Computer Vision.

[12]  Clark F. Olson,et al.  Automatic target recognition by matching oriented edge pixels , 1997, IEEE Trans. Image Process..

[13]  B. N. Chatterji,et al.  An FFT-based technique for translation, rotation, and scale-invariant image registration , 1996, IEEE Trans. Image Process..

[14]  Andriy Myronenko,et al.  Point Set Registration: Coherent Point Drift , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  T. Higuchi,et al.  High-Accuracy Subpixel Image Registration Based on Phase-Only Correlation , 2003, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[16]  Koichi Ito,et al.  A palmprint recognition algorithm using phase-based correspondence matching , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[17]  Rodney A. Kennedy,et al.  A Survey of Medical Image Registration on Multicore and the GPU , 2010, IEEE Signal Processing Magazine.

[18]  Dariu Gavrila,et al.  Real-time object detection for "smart" vehicles , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[19]  Carsten Steger,et al.  Similarity Measures for Occlusion, Clutter, and Illumination Invariant Object Recognition , 2001, DAGM-Symposium.

[20]  M. Druckmüller.  PHASE CORRELATION METHOD FOR THE ALIGNMENT OF TOTAL SOLAR ECLIPSE IMAGES , 2009 .

[21]  Andrew W. Fitzgibbon.  Robust registration of 2D and 3D point sets , 2003, Image Vis. Comput..

[22]  Jonathan T. Barron,et al.  A category-level 3-D object dataset: Putting the Kinect to work , 2011, ICCV Workshops.

[23]  Ko Nishino,et al.  Scale-hierarchical 3D object recognition in cluttered scenes , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[24]  Bernt Schiele,et al.  Robust Object Detection with Interleaved Categorization and Segmentation , 2008, International Journal of Computer Vision.

[25]  Federico Tombari,et al.  Performance Evaluation of 3D Keypoint Detectors , 2012, International Journal of Computer Vision.

[26]  Hui Chen,et al.  3D free-form object recognition in range images using local surface patches , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[27]  Nassir Navab,et al.  Model globally, match locally: Efficient and robust 3D object recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[28]  Robust Registration of 2 D and 3 D Point Sets , 2001 .