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A Visual Distance Approach for Multicamera Deployment With Coverage Optimization | IEEE Journals & Magazine | IEEE Xplore

A Visual Distance Approach for Multicamera Deployment With Coverage Optimization


Abstract:

This paper proposes a visual distance approach for a multicamera deployment through parallel coverage optimization over three-dimensional (3-D) space to inspect 3-D objec...Show More

Abstract:

This paper proposes a visual distance approach for a multicamera deployment through parallel coverage optimization over three-dimensional (3-D) space to inspect 3-D objects. The key idea is the proposal of a new “visual distance” between a single camera and a scene point, which takes into account multiple coverage criteria. Specifically, the effective visual sensing area of a single camera is expressed by a 4-D geometric object, which is composed of a 3-D visual frustum and an extra dimension for the acceptable view angle. An anisotropic projective transformation is applied to transform this 4-D geometric object into a 4-D unit cube, based on which a new visual coverage measure called “visual distance” is proposed using the infinity norm. It is shown that this new measure is capable of characterizing the coverage level of a task point in a quantitative way. Based on the visual distance, a coverage strength model and a new type of scene partition, called visual Voronoi partition, are established, and then a parallel gradient optimization approach is developed to achieve optimal coverage performance of a multicamera network. Comparative simulation and experimental results are provided to show the effectiveness and superior performance of the proposed approach.
Published in: IEEE/ASME Transactions on Mechatronics ( Volume: 23, Issue: 3, June 2018)
Page(s): 1007 - 1018
Date of Publication: 08 May 2018

ISSN Information:

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Author image of Xuebo Zhang
Institute of Robotics and Automatic Information System and Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China
Xuebo Zhang (M’12- SM’17) received the B.Eng. degree in automation from Tianjin University, Tianjin, China, in 2002 and the Ph.D. degree in control theory and control engineering from Nankai University, Tianjin, China, in 2011.
He is currently an Associate Professor with the Institute of Robotics and Automatic Information Systems, and Tianjin Key Laboratory of Intelligent Robotics, Nankai University, China. His resear...Show More
Xuebo Zhang (M’12- SM’17) received the B.Eng. degree in automation from Tianjin University, Tianjin, China, in 2002 and the Ph.D. degree in control theory and control engineering from Nankai University, Tianjin, China, in 2011.
He is currently an Associate Professor with the Institute of Robotics and Automatic Information Systems, and Tianjin Key Laboratory of Intelligent Robotics, Nankai University, China. His resear...View more
Author image of Xiang Chen
Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada
Xiang Chen (M’98) received the M.Sc. and Ph.D. degrees in systems and control from Louisiana State University, Baton Rouge, LA, USA, in 1996 and 1998, respectively.
Since 2000, he has been a Professor with the Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada. His research interests include robust control, vision sensor networks, vision-based control systems, networked control...Show More
Xiang Chen (M’98) received the M.Sc. and Ph.D. degrees in systems and control from Louisiana State University, Baton Rouge, LA, USA, in 1996 and 1998, respectively.
Since 2000, he has been a Professor with the Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada. His research interests include robust control, vision sensor networks, vision-based control systems, networked control...View more
Author image of Farsam Farzadpour
Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada
Farsam Farzadpour received the B.Sc. and M.Sc. degrees in mechanical engineering from Azad University, Khomeinishahr, Iran, in 2007 and 2011, respectively.
Since 2014, he has been working toward the Ph.D. degree in electrical and computer engineering at the University of Windsor, Windsor, ON, Canada. His research interests include mobile robotics, motion planning, optimization, computer vision, and sensor network deploy...Show More
Farsam Farzadpour received the B.Sc. and M.Sc. degrees in mechanical engineering from Azad University, Khomeinishahr, Iran, in 2007 and 2011, respectively.
Since 2014, he has been working toward the Ph.D. degree in electrical and computer engineering at the University of Windsor, Windsor, ON, Canada. His research interests include mobile robotics, motion planning, optimization, computer vision, and sensor network deploy...View more
Author image of Yongchun Fang
Institute of Robotics and Automatic Information System and Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China
Yongchun Fang (S’00 -M’02- SM’08) received the B.S. degree in electrical engineering and the M.S. degree in control theory and applications from Zhejiang University, Hangzhou, China, in 1996 and 1999, respectively, and the Ph.D. degree in electrical engineering from Clemson University, Clemson, SC, USA, in 2002.
From 2002 to 2003, he was a Postdoctoral Fellow with the Sibley School of Mechanical and Aerospace Enginee...Show More
Yongchun Fang (S’00 -M’02- SM’08) received the B.S. degree in electrical engineering and the M.S. degree in control theory and applications from Zhejiang University, Hangzhou, China, in 1996 and 1999, respectively, and the Ph.D. degree in electrical engineering from Clemson University, Clemson, SC, USA, in 2002.
From 2002 to 2003, he was a Postdoctoral Fellow with the Sibley School of Mechanical and Aerospace Enginee...View more

I. Introduction

As a typical kind of noncontact exteroceptive sensors, visual cameras present several extraordinary advantages, including rich information, low weight, small size, low power consumption, and low cost. Due to these attractive features, vision-based applications become more and more pervasive in the field of robotics, automation, and mechatronics [1]–[3]. Yet, a single camera cannot fully cover a three-dimensional (3-D) object due to its limited field of view (FOV) and visual occlusion. Hence, it is necessary to deploy a multicamera network [4] for many tasks, such as product quality inspection [5], dimension measurement [6], scene reconstruction [7], [8], visual surveillance [9], and so on.

Author image of Xuebo Zhang
Institute of Robotics and Automatic Information System and Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China
Xuebo Zhang (M’12- SM’17) received the B.Eng. degree in automation from Tianjin University, Tianjin, China, in 2002 and the Ph.D. degree in control theory and control engineering from Nankai University, Tianjin, China, in 2011.
He is currently an Associate Professor with the Institute of Robotics and Automatic Information Systems, and Tianjin Key Laboratory of Intelligent Robotics, Nankai University, China. His research interests include motion planning, visual servoing, SLAM, and visual sensor networks.
Xuebo Zhang (M’12- SM’17) received the B.Eng. degree in automation from Tianjin University, Tianjin, China, in 2002 and the Ph.D. degree in control theory and control engineering from Nankai University, Tianjin, China, in 2011.
He is currently an Associate Professor with the Institute of Robotics and Automatic Information Systems, and Tianjin Key Laboratory of Intelligent Robotics, Nankai University, China. His research interests include motion planning, visual servoing, SLAM, and visual sensor networks.View more
Author image of Xiang Chen
Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada
Xiang Chen (M’98) received the M.Sc. and Ph.D. degrees in systems and control from Louisiana State University, Baton Rouge, LA, USA, in 1996 and 1998, respectively.
Since 2000, he has been a Professor with the Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada. His research interests include robust control, vision sensor networks, vision-based control systems, networked control systems, and industrial applications of control theory.
Xiang Chen (M’98) received the M.Sc. and Ph.D. degrees in systems and control from Louisiana State University, Baton Rouge, LA, USA, in 1996 and 1998, respectively.
Since 2000, he has been a Professor with the Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada. His research interests include robust control, vision sensor networks, vision-based control systems, networked control systems, and industrial applications of control theory.View more
Author image of Farsam Farzadpour
Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada
Farsam Farzadpour received the B.Sc. and M.Sc. degrees in mechanical engineering from Azad University, Khomeinishahr, Iran, in 2007 and 2011, respectively.
Since 2014, he has been working toward the Ph.D. degree in electrical and computer engineering at the University of Windsor, Windsor, ON, Canada. His research interests include mobile robotics, motion planning, optimization, computer vision, and sensor network deployments.
Farsam Farzadpour received the B.Sc. and M.Sc. degrees in mechanical engineering from Azad University, Khomeinishahr, Iran, in 2007 and 2011, respectively.
Since 2014, he has been working toward the Ph.D. degree in electrical and computer engineering at the University of Windsor, Windsor, ON, Canada. His research interests include mobile robotics, motion planning, optimization, computer vision, and sensor network deployments.View more
Author image of Yongchun Fang
Institute of Robotics and Automatic Information System and Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China
Yongchun Fang (S’00 -M’02- SM’08) received the B.S. degree in electrical engineering and the M.S. degree in control theory and applications from Zhejiang University, Hangzhou, China, in 1996 and 1999, respectively, and the Ph.D. degree in electrical engineering from Clemson University, Clemson, SC, USA, in 2002.
From 2002 to 2003, he was a Postdoctoral Fellow with the Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA. He is currently a Professor with the Institute of Robotics and Automatic Information Systems, Nankai University, Tianjin, China. His research interests include AFM-based Nanosystems, visual servoing, and control of underactuated systems, including overhead cranes.
Yongchun Fang (S’00 -M’02- SM’08) received the B.S. degree in electrical engineering and the M.S. degree in control theory and applications from Zhejiang University, Hangzhou, China, in 1996 and 1999, respectively, and the Ph.D. degree in electrical engineering from Clemson University, Clemson, SC, USA, in 2002.
From 2002 to 2003, he was a Postdoctoral Fellow with the Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA. He is currently a Professor with the Institute of Robotics and Automatic Information Systems, Nankai University, Tianjin, China. His research interests include AFM-based Nanosystems, visual servoing, and control of underactuated systems, including overhead cranes.View more

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