2017/06/20 by Luz María Martínez, Javier Ruiz-del-Solar, Javier Ruíz-del-Solar +2 · 1 citation
Computer Science · Engineering · Materials Science · #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Hand Gesture Recognition Systems #Human Pose and Action Recognition #Industrial Vision Systems and Defect Detection #Robotics (cs.RO) #Textile materials and evaluations #cs.CV #cs.RO
paper · pdf · doi:10.48550/arxiv.1706.06694
Accepted in the RoboCup Symposium 2017. Final version will be published at Springer
arxiv created 2017/06/20 · openalex publication_date 2017/06/20 · arxiv updated 2017/06/22 · openalex created_date 2022/10/05 · openalex updated_date 2026/07/28
In this work a system for recognizing grasp points in RGB-D images is proposed. This system is intended to be used by a domestic robot when deploying clothes lying at a random position on a table. By taking into consideration that the grasp points are usually near key parts of clothing, such as the waist of pants or the neck of a shirt. The proposed system attempts to detect these key parts first, using a local multivariate contour that adapts its shape accordingly. Then, the proposed system applies the Vessel Enhancement filter to identify wrinkles in the clothes, allowing to compute a roughness index for the clothes. Finally, by mixing (i) the key part contours and (ii) the roughness information obtained by the vessel filter, the system is able to recognize grasp points for unfolding a piece of clothing. The recognition system is validated using realistic RGB-D images of different cloth types.