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Stereo Vision-Based 3D Pose Estimation of Product Labels for Bin Picking
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 Title & Authors
Stereo Vision-Based 3D Pose Estimation of Product Labels for Bin Picking
Udaya, Wijenayake; Choi, Sung-In; Park, Soon-Yong;
 
 Abstract
In the field of computer vision and robotics, bin picking is an important application area in which object pose estimation is necessary. Different approaches, such as 2D feature tracking and 3D surface reconstruction, have been introduced to estimate the object pose accurately. We propose a new approach where we can use both 2D image features and 3D surface information to identify the target object and estimate its pose accurately. First, we introduce a label detection technique using Maximally Stable Extremal Regions (MSERs) where the label detection results are used to identify the target objects separately. Then, the 2D image features on the detected label areas are utilized to generate 3D surface information. Finally, we calculate the 3D position and the orientation of the target objects using the information of the 3D surface.
 Keywords
bin picking;stereo vision;MSER;pose estimation;
 Language
English
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