Transparent object detection and location based on RGB-D camera

Citations Over TimeTop 10% of 2019 papers

Abstract

In order to improve the accuracy and efficiency of robot grasping, we propose a new method for transparent object detection and location that utilize depth image, RGB image and IR image. In detection process, an active depth sensor (RealSense) is firstly employed to retrieve the transparent candidates from the depth image and the corresponding candidates in the RGB image and IR image are then extracted separately. A transparent candidate classification algorithm is subsequently presented that uses SIFT features to recognize the transparent ones from the candidates. In location process, we obtain a new group of RGB images and IR images by adjusting camera orientation to make its optical axis perpendicular to the normal direction of the plane on which the object is placed. The object contours in RGB image and IR image are then extracted, respectively. The three-dimensional object is finally reconstructed by means of stereo matching of the two contours, and the current pose information of the object is calculated in the end. In order to verify the feasibility of the method, we built a hand-eye test system with a movable industrial robot to detect and capture transparent objects at different locations. The final test results demonstrate that the method is more general and effective than the traditional one.

Related Papers

• Survey of Feature Points Detection and Matching using SURF, SIFT and PCA-SIFT(2014)
• → Improvements of Local Descriptor in HOG/SIFT by BOF Approach(2014)5 cited
• → Implementation of Image Matching Algorithm Based on SIFT Features(2014)3 cited
• Application of multiple-layer SIFT to semantic concept detection(2011)
• → Performance Improvement of SIFT-based Copy-move Forgery Detection Using CSLBP Descriptor(2020)