Abstract
For modern assistance systems, time of flight (tof) cameras play a key role in the perception of the environmental situation. Due to benefits of this sensor type, especially in combination with video sensors, it outperforms typical sensor systems, like stereo cameras. However, tof depth image segmentation is yet not solved satisfactorily. Common approaches use homogeneous constraints and therefore assume objects to be parallel to the camera plane. This consequently leads to segmentation errors. This paper proposes a fast segmentation algorithm for detecting distinct planes using statistical knowledge. By projecting the depth image data along the image axis, u-v-histogram images can be constructed. It is shown, that in the histogram images, 3D planes correspond to line segments. A fast approach for line segment extraction in the histogram images is used to find the relevant planes. The algorithm was successfully tested with real data under varying conditions and can be applied for different tof camera sensors.
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Schamm, T., Rönnau, A., Zöllner, J.M. (2010). Fast 3D Time of Flight Data Segmentation Using the U-V-Histogram Approach. In: Liu, H., Ding, H., Xiong, Z., Zhu, X. (eds) Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science(), vol 6424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16584-9_60
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DOI: https://doi.org/10.1007/978-3-642-16584-9_60
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