Abstract
Category-level object detection, the task of locating object instances of a given category in images, has been tackled with many algorithms employing standard color images. Less attention has been given to solving it using range and depth data, which has lately become readily available using laser and RGB-D cameras. Exploiting the different nature of the depth modality, we propose a novel shape-based object detector with partial pose estimation for axial or reflection symmetric objects. We estimate this partial pose by detecting target’s symmetry, which as a global mid-level feature provides us with a robust frame of reference with which shape features are represented for detection. Results are shown on a particularly challenging depth dataset and exhibit significant improvement compared to the prior art.
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Aldoma, A., Vincze, M., Blodow, N., Gossow, D., Gedikli, S., Rusu, R., Bradski, G.: Cad-model recognition and 6dof pose estimation using 3d cues. In: IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 585–592 (2011)
Bo, L., Lai, K., Ren, X., Fox, D.: Object recognition with hierarchical kernel descriptors. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1729–1736. IEEE (2011)
Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2(3), 27:1–27:27 (2011)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 886–893 (2005)
Everingham, M., Van Gool, L., Williams, C., Winn, J., Zisserman, A.: The pascal visual object classes (voc) challenge. International Journal of Computer Vision 88(2), 303–338 (2010)
Felzenszwalb, P., McAllester, D., Ramanan, D.: A discriminatively trained, multiscale, deformable part model. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
Hinterstoisser, S., Holzer, S., Cagniart, C., Ilic, S., Konolige, K., Navab, N., Lepetit, V.: Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 858–865 (2011)
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 Transactions on Pattern Analysis and Machine Intelligence 34(5), 876–888 (2012)
Janoch, A., Karayev, S., Jia, Y., Barron, J., Fritz, M., Saenko, K., Darrell, T.: A category-level 3-d object dataset: Putting the kinect to work. In: Consumer Depth Cameras for Computer Vision (2011)
Kim, B., Xu, S., Savarese, S.: Accurate localization of 3d objects from rgb-d data using segmentation hypotheses. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 886–893 (2013)
Lai, K., Bo, L., Ren, X., Fox, D.: A large-scale hierarchical multi-view rgb-d object dataset. In: Proceedings of the IEEE International Conference on Robotics and Automation (2011)
Lai, K., Bo, L., Ren, X., Fox, D.: Sparse distance learning for object recognition combining rgb and depth information. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 4007–4013 (2011)
Lai, K., Bo, L., Ren, X., Fox, D.: Detection-based object labeling in 3d scenes. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1330–1337 (2012)
Lee, S., Liu, Y.: Curved glide-reflection symmetry detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(2), 266–278 (2012)
Lin, Z., Davis, L.S.: A pose-invariant descriptor for human detection and segmentation. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 423–436. Springer, Heidelberg (2008)
Loy, G., Eklundh, J.-O.: Detecting symmetry and symmetric constellations of features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 508–521. Springer, Heidelberg (2006)
Mitra, N., Pauly, M., Wand, M., Ceylan, D.: Symmetry in 3d geometry: Extraction and applications. In: EUROGRAPHICS State-of-the-art Report (2012)
Park, M., Lee, S., Chen, P., Kashyap, S., Butt, A., Liu, Y.: Performance evaluation of state-of-the-art discrete symmetry detection algorithms. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
Podolak, J., Shilane, P., Golovinskiy, A., Rusinkiewicz, S., Funkhouser, T.: A planar-reflective symmetry transform for 3d shapes. ACM Transactions on Graphics 25(3), 549–559 (2006)
Raviv, D., Bronstein, A., Bronstein, M., Kimmel, R.: Symmetries of non-rigid shapes. In: Non-rigid Registration and Tracking through Learning workshop (NRTL), IEEE International Conference on Computer Vision (ICCV), pp. 1–7 (2007)
Redondo-Cabrera, C., López-Sastre, R., Acevedo-Rodriguez, J., Maldonado-Bascón, S.: Surfing the point clouds: Selective 3d spatial pyramids for category-level object recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3458–3465 (2012)
Rusu, R.: Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments. Ph.D. thesis, Technische Universitaet Muenchen, Germany (2009)
Saenko, K., Karayev, S., Jia, Y., Shyr, A., Janoch, A., Long, J., Fritz, M., Darrell, T.: Practical 3-d object detection using category and instance-level appearance models. In: IEEE International Workshop on Intelligent Robots and Systems, pp. 1817–1824 (2011)
Shotton, J., Sharp, T., Kipman, A., Fitzgibbon, A., Finocchio, M., Blake, A., Cook, M., Moore, R.: Real-time human pose recognition in parts from single depth images. Communication of the ACM 56(1), 116–124 (2013)
Silberman, N., Fergus, R.: Indoor scene segmentation using a structured light sensor. In: IEEE International Conference on Computer Vision Workshops, ICCV Workshops (2011)
Spinello, L., Arras, K.: People detection in rgb-d data. In: IEEE International Workshop on Intelligent Robots and Systems, pp. 3838–3843 (2011)
Tang, S., Wang, X., Lv, X., Han, T.X., Keller, J., He, Z., Skubic, M., Lao, S.: Histogram of oriented normal vectors for object recognition with a depth sensor. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds.) ACCV 2012, Part II. LNCS, vol. 7725, pp. 525–538. Springer, Heidelberg (2013)
Thrun, S., Wegbreit, B.: Shape from symmetry. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1824–1831 (2005)
Zhao, P., Quan, L.: Translation symmetry detection in a fronto-parallel view. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1009–1016 (2011)
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Barnea, E., Ben-Shahar, O. (2014). Depth Based Object Detection from Partial Pose Estimation of Symmetric Objects. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds) Computer Vision – ECCV 2014. ECCV 2014. Lecture Notes in Computer Science, vol 8693. Springer, Cham. https://doi.org/10.1007/978-3-319-10602-1_25
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DOI: https://doi.org/10.1007/978-3-319-10602-1_25
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