Improved Fourier descriptors in model-based pose estimation

Hui-jun Tang; Jia Wen; Cai-wen Ma; Hai-bin Hu; Ren-kui Zhou

doi:10.1117/12.901770

2 December 2011 Improved Fourier descriptors in model-based pose estimation

Hui-jun Tang, Jia Wen, Cai-wen Ma, Hai-bin Hu, Ren-kui Zhou

Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 80040M (2011) https://doi.org/10.1117/12.901770
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

We use Fourier descriptors (FD's) to represent shape in model-based pose estimation. Specific invariance and normalization requirements for shape descriptors concerning to pose estimation are proposed. FD's are improved to meet such requirements. Common issues and techniques for such application are focused on. Starting point of the shape contour is fixed to the upper left corner point. Distance pairs instead of edge coordinate pairs recast the shape sequence. Moving average filtering is proceeded to remove the noises of the shape sequence. Shape sequence is re-sampled to make it definite length. FD's amplitude is normalized to the range of 0 to 1. Variance of sequences between observed and library FD's is defined as the shape matching objective function. For simulation, we use a missile model of Milkshape3d format. Results show that by adopting the improved FD's, we can arrive at a pose estimation practically by randomly optimal search of library FD's.

Citation Download Citation

Hui-jun Tang, Jia Wen, Cai-wen Ma, Hai-bin Hu, and Ren-kui Zhou "Improved Fourier descriptors in model-based pose estimation", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040M (2 December 2011); https://doi.org/10.1117/12.901770

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