1. 燕山大学信息科学与工程学院,河北,秦皇岛,066004
2. 河北省计算机虚拟技术与系统集成重点实验室,河北,秦皇岛,066004
3. 燕山大学信息科学与工程学院,河北,秦皇岛,066004
4. 河北省计算机虚拟技术与系统集成重点实验室,河北,秦皇岛,066004
网络出版:2016-02-25,
纸质出版:2016
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张世辉, 张钰程. 基于单幅深度图像遮挡信息的下一最佳观测方位确定方法[J]. 电子学报, 2016,44(2):445-452.
ZHANG Shi-hui, ZHANG Yu-cheng. Determining Next Best View Based on Occlusion Information of a Single Depth Image[J]. Acta Electronica Sinica, 2016, 44(2): 445-452.
张世辉, 张钰程. 基于单幅深度图像遮挡信息的下一最佳观测方位确定方法[J]. 电子学报, 2016,44(2):445-452. DOI: 10.3969/j.issn.0372-2112.2016.02.028.
ZHANG Shi-hui, ZHANG Yu-cheng. Determining Next Best View Based on Occlusion Information of a Single Depth Image[J]. Acta Electronica Sinica, 2016, 44(2): 445-452. DOI: 10.3969/j.issn.0372-2112.2016.02.028.
如何根据当前观测到的信息确定摄像机的下一最佳观测方位是视觉领域一个具有挑战性的问题.本文提出一种基于单幅深度图像利用遮挡信息求解下一最佳观测方位的方法.该方法首先利用当前观测方位下获得的深度图像中的遮挡信息对遮挡区域外接表面进行四边形剖分
从而建立遮挡区域外接表面模型;然后通过综合考虑下一观测过程中的可见四边形信息以及观测损失信息构造下一最佳观测方位模型;最后采用梯度下降法求解所建模型得到下一最佳观测方位.与已有方法相比
所提方法无需将摄像机位置固定于某一表面
也无需获取视觉目标的先验知识.实验结果验证了所提方法的可行性和有效性.
How to determine camera's next best view based on current information is a challenging problem in visual field.A next best view approach was proposed based on the occlusion information of a single depth image.Firstly
to establish the model for occlusion region external surface
the quadrilateral meshes for occlusion region external surface were obtained according to the occlusion information of a depth image in initial view.Secondly
the model for next best view was constructed by considering both the visible quadrangle and the loss information in next view.Finally
the next best view was achieved by solving the model with gradient descent method.Compared with the existing methods
the proposed approach does not limit the camera position on a fixed surface or need the priori knowledge of visual object.Experimental results demonstrate its feasibility and effectiveness.
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