Abstract
This paper investigates the problem of object segmentation in cluttered environment. This problem enables a large variety of exciting and important applications. An interactive perception method is proposed to segment scene into constituent objects based on principal angle. Trajectory data of feature points reflecting the essence of scene structure changes is extracted by a robot arm to calculate least stable regions for the interactive task. The segmentation task is achieved by the principal angle of stable regions because the principal angle essentially estimates the similarity between two regions. In contrast to probability based approach, our method performs well on efficiency of segmentation as it works without estimating parameters of the system. Experimental results on real world scene confirm the effectiveness of our method.
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Wu, R., Zhao, D., Liu, J., Tang, X., Huang, Q. (2017). Autonomous Object Segmentation in Cluttered Environment Through Interactive Perception. In: Sun, Y., Lu, H., Zhang, L., Yang, J., Huang, H. (eds) Intelligence Science and Big Data Engineering. IScIDE 2017. Lecture Notes in Computer Science(), vol 10559. Springer, Cham. https://doi.org/10.1007/978-3-319-67777-4_30
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DOI: https://doi.org/10.1007/978-3-319-67777-4_30
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