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The problem of 3D pose recognition of a rigid object is difficult to solve because the pose in a 3D space can vary with multiple degrees of freedom. In this work, we propose an accurate method for 3D pose estimation based on template matched filtering. The proposed method utilizes a bank of space-variant filters which take into account different pose states of the target and local statistical properties of the input scene. The state parameters of location coordinates, orientation angles, and scaling parameters of the target are estimated with high accuracy in the input scene. Experimental tests are performed for real and synthetic scenes. The proposed system yields good performance for 3D pose recognition in terms of detection efficiency, location and orientation errors.
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Kenia Picos, Víctor H. Díaz-Ramírez, "Pose detection of a 3D object using template matched filtering," Proc. SPIE 9970, Optics and Photonics for Information Processing X, 99700S (14 September 2016); https://doi.org/10.1117/12.2237409