Do We Need Binary Features for 3D Reconstruction?

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	Do We Need Binary Features for 3D Reconstruction?
	Bin Fan; Qingqun Kong; Wei Sui; Zhiheng Wang; Xinchao Wang; Shiming Xiang; Chunhong Pan; Pascal Fua
	2016
会议名称	Conference on Computer Vision and Pattern Recognition
会议日期	2016-6
会议地点	Las Vegas, USA
摘要	Binary features have been incrementally popular in the past few years due to their low memory footprints and the efficient computation of Hamming distance between binary descriptors. They have been shown with promising results on some real time applications, e.g., SLAM, where the matching operations are relative few. However, in computer vision, there are many applications such as 3D reconstruction requiring lots of matching operations between local features. Therefore, a natural question is that is the binary feature still a promising solution to this kind of applications? To get the answer, this paper conducts a comparative study of binary features and their matching methods on the context of 3D reconstruction in a recently proposed large scale mutliview stereo dataset. Our evaluations reveal that not all binary features are capable of this task. Most of them are inferior to the classical SIFT based method in terms of reconstruction accuracy and completeness with a not significant better computational performance.
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/20370
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
推荐引用方式 GB/T 7714	Bin Fan,Qingqun Kong,Wei Sui,et al. Do We Need Binary Features for 3D Reconstruction?[C],2016.

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