Abstract
This paper proposes a fast template matching strategy for real-time pose estimation of texture-less objects in a single camera image. The key novelty is the hierarchical searching strategy through a template pyramid. Firstly, a model database whose templates are stored in a hierarchical pyramid need to be generated offline. The online hierarchical searching through the template pyramid is computed to collect all candidate templates which pass the similarity measure criterion. All of the template candidates and their child neighbor templates are tracked down to the next lower level of pyramid. This hierarchical tracking process is repeated until all template candidates have been tracked down to the lowest level of pyramid. The experimental result shows that the runtime of template matching procedure in the state-of-the-art LINE2D approach [1] after applying our fast hierarchical searching strategy is 44 times faster than the original LINE2D searching method while the database contains 15120 templates.
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References
Hinterstoisser, S., Cagniart, C., Ilic, S., Sturm, P., Navab, N., Fua, P., Lepetit, V.: Gradient response maps for real-time detection of textureless objects. IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 876–888 (2012)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)
Bay, H., Tuytelaars, T., Van Gool, L.: Surf: speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part I. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to SIFT or SURF. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 2564–2571. IEEE, November 2011
Alahi, A., Ortiz, R., Vandergheynst, P.: Freak: fast retina keypoint. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 510–517. IEEE, June 2012
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1, pp. 886–893. IEEE, June 2005
Fitzgibbon, A.W.: Robust registration of 2D and 3D point sets. Image Vis. Comput. 21(13), 1145–1153 (2003)
Hinterstoisser, S., Lepetit, V., Ilic, S., Holzer, S., Bradski, G., Konolige, K., Navab, N.: Model based training, detection and pose estimation of texture-less 3D objects in heavily cluttered scenes. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds.) ACCV 2012, Part I. LNCS, vol. 7724, pp. 548–562. Springer, Heidelberg (2013)
Steger, C.: Occlusion, clutter, and illumination invariant object recognition. Int. Arch. Photogrammetry Remote Sens. Spat. Inf. Sci. 34(3/A), 345–350 (2002)
Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(6), 679–698 (1986)
Acknowledgments
This research was supported in part by National Key Basic Research Program of China under Grant 2013CB035804 and National Natural Science Foundation of China under Grant U1201244.
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Ye, C., Li, K., Jia, L., Zhuang, C., Xiong, Z. (2016). Fast Hierarchical Template Matching Strategy for Real-Time Pose Estimation of Texture-Less Objects. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9834. Springer, Cham. https://doi.org/10.1007/978-3-319-43506-0_19
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DOI: https://doi.org/10.1007/978-3-319-43506-0_19
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