Parallel vision for perception and understanding of complex scenes: methods, framework, and perspectives
Wang, Kunfeng1; Gou, Chao1; Zheng, Nanning2; Rehg, James M.3; Wang, Fei-Yue1,4
2017-10-01
发表期刊ARTIFICIAL INTELLIGENCE REVIEW
卷号48期号:3页码:299-329
文章类型Article
摘要
; In the study of image and vision computing, the generalization capability of an algorithm often determines whether it is able to work well in complex scenes. The goal of this review article is to survey the use of photorealistic image synthesis methods in addressing the problems of visual perception and understanding. Currently, the ACP Methodology comprising artificial systems, computational experiments, and parallel execution is playing an essential role in modeling and control of complex systems. This paper extends the ACP Methodology into the computer vision field, by proposing the concept and basic framework of Parallel Vision. In this paper, we first review previous works related to Parallel Vision, in terms of synthetic data generation and utilization. We detail the utility of synthetic data for feature analysis, object analysis, scene analysis, and other analyses. Then we propose the basic framework of Parallel Vision, which is composed of an ACP trilogy (artificial scenes, computational experiments, and parallel execution). We also present some in-depth thoughts and perspectives on Parallel Vision. This paper emphasizes the significance of synthetic data to vision system design and suggests a novel research methodology for perception and understanding of complex scenes.
关键词Visual Perception Complex Scenes Parallel Vision Acp Methodology Computer Graphics Image Synthesis
WOS标题词Science & Technology ; Technology
DOI10.1007/s10462-017-9569-z
关键词[WOS]PEDESTRIAN DETECTION ; VIDEO SURVEILLANCE ; DOMAIN ADAPTATION ; CAMERA NETWORKS ; COMPUTER VISION ; VIRTUAL WORLDS ; RECOGNITION ; IMAGES ; ALGORITHMS ; MACHINES
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61533019 ; 71232006)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000412658700001
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20082
专题复杂系统管理与控制国家重点实验室_先进控制与自动化
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Xi An Jiao Tong Univ, IAIR, Xian 710049, Shaanxi, Peoples R China
3.Georgia Inst Technol, Sch Interact Comp, Atlanta, GA 30332 USA
4.Natl Univ Def Technol, Res Ctr Computat Expt & Parallel Syst Tech, Changsha 410073, Hunan, Peoples R China
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Wang, Kunfeng,Gou, Chao,Zheng, Nanning,et al. Parallel vision for perception and understanding of complex scenes: methods, framework, and perspectives[J]. ARTIFICIAL INTELLIGENCE REVIEW,2017,48(3):299-329.
APA Wang, Kunfeng,Gou, Chao,Zheng, Nanning,Rehg, James M.,&Wang, Fei-Yue.(2017).Parallel vision for perception and understanding of complex scenes: methods, framework, and perspectives.ARTIFICIAL INTELLIGENCE REVIEW,48(3),299-329.
MLA Wang, Kunfeng,et al."Parallel vision for perception and understanding of complex scenes: methods, framework, and perspectives".ARTIFICIAL INTELLIGENCE REVIEW 48.3(2017):299-329.
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