Extracting the three-dimensional (3D) information including location and height of a pedestrian is important for vision-based intelligent traffic monitoring systems. This paper tackles the relationship between pixels′ actual size and pixels′ spatial resolution through a new method named pixel-resolution mapping (P-RM). The proposed P-RM method derives the equations for pixels′ spatial resolutions (XY-direction) and object′s height (Z-direction) in the real world, while introducing new tilt angle and mounting height calibration methods that do not require special calibration patterns placed in the real world. Both controlled laboratory and actual world experiments were performed and reported. The tests on 3D mensuration using proposed P-RM method showed overall better than 98.7% accuracy in laboratory environments and better than 96% accuracy in real world pedestrian height estimations. The 3D reconstructed images for measured points were also determined with the proposed P-RM method which shows that the proposed method provides a general algorithm for 3D information extraction.
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Recommended by Associate Editor De Xu
Bing-Xing Wu received the B. Eng. degree in electrical engineering from Shanghai University of Electric Power, China in 2012, the M. Eng. and Ph. D. degrees in electrical engineering from University of Idaho, USA in 2014 and 2018, respectively. He is currently a lecturer and electric microscope expert in Department of Electrical and Computer Engineering, University of Idaho, USA.
His research interests include CMOS image sensor design, digital image processing, machine vision, and vision based traffic detection.
Suat Utku Ay received the M. Sc. and Ph. D. degrees in electrical engineering from the University of Southern California (USC), USA in 1997 and 2005, respectively. His Ph. D. thesis involved designing large format scientific CMOS image sensors for space applications. From September 1997 to July 2007, he was working in the industry as VLSI design engineer specializing in the area of mixed-signal very large scale integration (VLSI) design and CMOS image sensors. He was with Photobit Corporation which later became the Micron Technology Inc.′s Imaging Division in 2001 and Aptina Imaging in 2008 and On Semiconductor in 2015. He joined the Department of Electrical and Computer Engineering, University of Idaho, USA, on August 2007 as an assistant professor and become an associate professor in 2013. He is a member of the IEEE Solid State Circuits, IEEE Circuits and Systems, IEEE Electron Devices, and Society of Photo-optical Instrumentation (SPIE) societies.
His research interests include VLSI analog and mixed-signal integrated circuit (IC) design techniques for new class of baseband and radio frequency (RF) circuits and systems, on intelligent sensor systems with emphasis of reconfigurable, secure, flexible electro-optical circuit and devices, and on self-sustained and smart CMOS sensors for remote wireless network and systems.
Ahmed Abdel-Rahim is a professor in the Civil & Environmental Engineering Department at the University of Idaho, USA and the director of the University′s National Institute for Advanced Transportation Technology (NIATT), USA. He earned his doctorate in transportation engineering from Michigan State University, USA in 1998. He has published more than 50 refereed publications and has over 20 years of experience managing research projects. He is the lead principal investigator and the director of the University of Idaho′s University Transportation Center, USA that focuses on Transportation for Livability by Integrating the Vehicle and the Environment (TranLIVE).
His research interests include connected vehicle applications, modeling the environmental impact of vehicle operations, intelligent transportation systems (ITS), traffic operations and control technology, traffic modeling, security and survivability of transportation networks, and highway traffic safety.
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Wu, BX., Ay, S.U. & Abdel-Rahim, A. Pedestrian Height Estimation and 3D Reconstruction Using Pixel-resolution Mapping Method Without Special Patterns. Int. J. Autom. Comput. 16, 449–461 (2019). https://doi.org/10.1007/s11633-019-1170-2
- Traffic monitoring application
- spatial resolution
- pixel-resolution mapping (P-RM) method
- 3D information
- pedestrian height estimation