Supervised preserving projection for learning scene information based on time-of-flight imaging sensor

CORC > 厦门大学 > 信息技术－已发表论文

	Supervised preserving projection for learning scene information based on time-of-flight imaging sensor
	Jiang, Yi ; Liu, Yong ; Lei, Yunqi ; Wang, Qicong ; Lei YQ(雷蕴奇) ; Wang QC(王其聪)
刊名	http://dx.doi.org/10.1364/AO.52.005279
	2013
关键词	NONLINEAR DIMENSIONALITY REDUCTION FRAMEWORK
英文摘要	National Natural Science Foundation of China [61001143]; Key Project Funds from the Province Office of Science & Technology of Fujian in China [2012H6024]; In this paper, we propose a new supervised manifold learning approach, supervised preserving projection (SPP), for the depth images of a 3D imaging sensor based on the time-of-flight (TOF) principle. We present a novel manifold sense to learn scene information produced by the TOF camera along with depth images. First, we use a local surface patch to approximate the underlying manifold structures represented by the scene information. The fundamental idea is that, because TOF data have nonstatic noise and distance ambiguity problems, the surface patches can more efficiently approximate the local neighborhood structures of the underlying manifold than TOF data points, and they are robust to the nonstatic noise of TOF data. Second, we propose SPP to preserve the pairwise similarity between the local neighboring patches in TOF depth images. Moreover, SPP accomplishes the low-dimensional embedding by adding the scene region class label information accompanying the training samples and obtains the predictive mapping by incorporating the local geometrical properties of the dataset. The proposed approach has advantages of both classical linear and nonlinear manifold learning, and real-time estimation results of the test samples are obtained by the low-dimensional embedding and the predictive mapping. Experiments show that our approach obtains information effectively from three scenes and is robust to the nonstatic noise of 3D imaging sensor data. (c) 2013 Optical Society of America
语种	英语
出版者	OPTICAL SOC AMER
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/92555]
专题	信息技术－已发表论文
推荐引用方式 GB/T 7714	Jiang, Yi,Liu, Yong,Lei, Yunqi,et al. Supervised preserving projection for learning scene information based on time-of-flight imaging sensor[J]. http://dx.doi.org/10.1364/AO.52.005279,2013.
APA	Jiang, Yi,Liu, Yong,Lei, Yunqi,Wang, Qicong,雷蕴奇,&王其聪.(2013).Supervised preserving projection for learning scene information based on time-of-flight imaging sensor.http://dx.doi.org/10.1364/AO.52.005279.
MLA	Jiang, Yi,et al."Supervised preserving projection for learning scene information based on time-of-flight imaging sensor".http://dx.doi.org/10.1364/AO.52.005279 (2013).