Automatic and Accurate 3D Measurement Based on RGBD Saliency Detection

The 3D measurement is widely required in modern industries. In this letter, a method based on the RGBD saliency detection with depth range adjusting (RGBD-DRA) is proposed for 3D measurement. By using superpixels and prior maps, RGBD saliency detection is utilized to detect and measure the target object automatically Meanwhile, the proposed depth range adjusting is processing while measuring to prompt the measuring accuracy further. The experimental results demonstrate the proposed method automatic and accurate, with 3 mm and 3.77% maximum deviation value and rate, respectively. key words: 3D measurement, RGBD saliency detection, saliency map, depth range adjusting, superpixel

[1]  K. Madhava Krishna,et al.  Depth really Matters: Improving Visual Salient Region Detection with Depth , 2013, BMVC.

[2]  Pascal Fua,et al.  SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Harish Katti,et al.  Depth Matters: Influence of Depth Cues on Visual Saliency , 2012, ECCV.

[4]  Michael Ying Yang,et al.  Exploiting global priors for RGB-D saliency detection , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[5]  Ali Borji,et al.  Salient Object Detection: A Benchmark , 2015, IEEE Transactions on Image Processing.