An Integrated Framework for 3-D Modeling, Object Detection, and Pose Estimation From Point-Clouds

作者：Guo, Yulan^*; Bennamoun, Mohammed; Sohel, Ferdous; Lu, Min; Wan, Jianwei

来源：IEEE Transactions on Instrumentation and Measurement, 2015, 64(3): 683-693.

DOI：10.1109/TIM.2014.2358131

• 3-D modeling
• 3-D object detection
• 3-D object recognition
• point-cloud
• pose estimation
• range image

3-D modeling, object detection, and pose estimation are three of the most challenging tasks in the area of 3-D computer vision. This paper presents a novel algorithm to perform these tasks simultaneously from unordered point-clouds. Given a set of input point-clouds in the presence of clutter and occlusion, an initial model is first constructed by performing pair-wise registration between any two point-clouds. The resulting model is then updated from the remaining point-clouds using a novel model growing technique. Once the final model is reconstructed, the instances of the object are detected and the poses of its instances in the scenes are estimated. This algorithm is automatic, model free, and does not rely on any prior information about the objects in the scene. The algorithm was comprehensively tested on the University of Western Australia data set. Experimental results show that our algorithm achieved accurate modeling, detection, and pose estimation performance.

• 出版日期2015-3
• 单位中国人民解放军国防科学技术大学