CASIA OpenIR  > 模式识别国家重点实验室  > 机器人视觉
Batched Incremental Structure-from-Motion
Cui Hainan(崔海楠); Shuhan Shen(申抒含); Gao Xiang(高翔); Hu Zhanyi(胡占义)
2017
会议名称International Conference on 3D Vision
会议日期2017-10
会议地点QingDao, China
摘要
The incremental Structure-from-Motion (SfM) technique
has advanced in both robustness and accuracy, but the effi-
ciency and scalability remain its key challenges. In this pa-
per, we propose a novel batched incremental SfM technique
to tackle these problems in a unified framework, where two
iteration loops are contained. The inner loop is a tracks tri-
angulation loop, where a novel tracks selection method is
proposed to find a compact subset of tracks for the bundle
adjustment (BA). The outer loop is a camera registration
loop, where a batch of cameras are simultaneously added
to alleviate the drifting risk and reduce the running times
of BA. By the tracks selection and batched camera registra-
tion, we find these two iteration loops converge fast. Ex-
tensive experiments demonstrate that our new SfM system
performs similarly or better than many of the state-of-the-
art SfM systems in terms of camera calibration accuracy,
while is more efficient, robust and scalable for large-scale
scene reconstruction.
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/19771
专题模式识别国家重点实验室_机器人视觉
推荐引用方式
GB/T 7714
Cui Hainan,Shuhan Shen,Gao Xiang,et al. Batched Incremental Structure-from-Motion[C],2017.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
HainanCui_3DV2017.pd(1637KB)会议论文 开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Cui Hainan(崔海楠)]的文章
[Shuhan Shen(申抒含)]的文章
[Gao Xiang(高翔)]的文章
百度学术
百度学术中相似的文章
[Cui Hainan(崔海楠)]的文章
[Shuhan Shen(申抒含)]的文章
[Gao Xiang(高翔)]的文章
必应学术
必应学术中相似的文章
[Cui Hainan(崔海楠)]的文章
[Shuhan Shen(申抒含)]的文章
[Gao Xiang(高翔)]的文章
相关权益政策
暂无数据
收藏/分享
文件名: HainanCui_3DV2017.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。