融合粗糙深度信息的低纹理物体偏振三维重建
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1.北京大学 空间信息集成与3S工程应用北京市重点实验室, 北京 100871;2.北京大学 地球与空间科学学院 遥感与地理信息系统研究所, 北京 100871;3.北京大学 数字视频编解码技术国家工程实验室, 北京;100871

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基金项目:

国家重点研发计划 2017YFB0503004;国家自然科学基金 41842048国家重点研发计划(2017YFB0503004),国家自然科学基金(41842048)


Shape from Polarization of low-texture objects with rough depth information
Author:
Affiliation:

1.Beijing Key Laboratory of Spatial Information Integration and 3S Application, Peking University, Beijing 100871, China;2.Institute of Remote Sensing and Geographic Information System, School of Earth and Space Science, Peking University, Beijing 100871, China;3.National Engineering Laboratory for Video Technology, Peking University, Beijing 100871, China

Fund Project:

National Key R&D Program of China 2017YFB0503000;National Natural Science Foundation of China 41842048Supported by National Key R&D Program of China(2017YFB0503000),National Natural Science Foundation of China(41842048)

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    摘要:

    对于表面光滑、低纹理的目标,传统基于多视几何重建的算法难以获得理想的结果,利用偏振信息来重建这类物体是便捷有效的方法之一.然而单纯利用偏振信息进行三维重建存在歧义性等问题,难以获得理想的结果.以粗糙深度图作为先验信息可解决歧义性问题.先对偏振相机与深度相机标定并配准图像,由粗糙深度图获得的法向量辅助纠正偏振方位角歧义,再利用纠正的法向量与粗糙深度图积分融合,从而获得较高精度的物体三维表面.

    Abstract:

    For the smooth surface and low-texture target, the traditional multi-view geometry reconstruction algorithm was difficult to obtain the ideal result. However, it is difficult to obtain ideal results by simply using the polarization information for three-dimensional reconstruction with ambiguity problem. Using the rough depth map as a prior information can solve the azimuth ambiguity problem. Firstly, calibrated and aligned the polarized camera and the depth camera, and used the normal vector obtained by the rough depth map to correct the polarization azimuth ambiguity, then integrated the corrected normal vector with the rough depth map to obtain a high-precision three-dimensional surface of the object.

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杨锦发,晏磊,赵红颖,陈瑞,张瑞华,施柏鑫.融合粗糙深度信息的低纹理物体偏振三维重建[J].红外与毫米波学报,2019,38(6):819~827]. YANG Jin-Fa, YAN Lei, ZHAO Hong-Ying, CHEN Rui, ZHANG Rui-Hua, SHI Bo-Xin. Shape from Polarization of low-texture objects with rough depth information[J]. J. Infrared Millim. Waves,2019,38(6):819~827.]

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  • 收稿日期:2019-05-14
  • 最后修改日期:2019-11-13
  • 录用日期:2019-08-15
  • 在线发布日期: 2019-12-17
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