ITM Web Conf.
Volume 12, 2017The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|Number of page(s)||6|
|Section||Session 1: Robotics|
|Published online||05 September 2017|
3D Object Recognition Based on ADAPTIVE-SCALE and SPCA-ALM in Cluttered Scenes
School of Communication & Information Engineering, Institute of Smart City, Shanghai University, Shanghai, China
In this paper a novel 3D object recognition method which can improve the recognition accuracy of object recognition in the cluttered scenes was proposed. The proposed method use the adaptive-scale to detect the keypoint (ASDK) of 3D object in the cluttered scenes, it use the algorithm of Sparse Principal Component Analysis Augmented Lagrangian Method (SPCA-ALM) to extract the feature of object, the algorithm of SPCA-ALM has a good performance in the high dimensional due to the Spares PCA, and the ALM can raise the speed of the SPCA. The experiment shows that the proposed method can decrease the time of 3D object recognition and improve the recognition accuracy.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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