Vehicle detection in aerial images using multiscale structure enhancement and symmetry

Sundaresh Ram; Jeffrey J Rodriguez

doi:10.1109/ICIP.2016.7533074

Vehicle detection in aerial images using multiscale structure enhancement and symmetry

Sundaresh Ram, Jeffrey J Rodriguez

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

Accurate detection and localization of vehicles in aerial images has a wide range of applications including urban planning, military reconnaissance, visual surveillance, and realtime traffic management. Automated detection of vehicles in aerial imagery is a challenging task, due to the density of vehicles on the road, the complexity of the surrounding environment in urban areas, and low spatial resolution of the image sensor array. We propose an automated method for detecting vehicles of varying sizes in low-resolution aerial imagery. First, we develop a new vehicle enhancement filter involving multiscale Hessian analysis. After thresholding, we refine the candidate vehicle detections based on analysis of bilateral symmetry. We show that our proposed method provides improved detection accuracy compared with existing vehicle detection algorithms for various low-resolution aerial images.

Original language	English (US)
Title of host publication	2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
Publisher	IEEE Computer Society
Pages	3817-3821
Number of pages	5
Volume	2016-August
ISBN (Electronic)	9781467399616
DOIs	https://doi.org/10.1109/ICIP.2016.7533074
State	Published - Aug 3 2016
Event	23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States Duration: Sep 25 2016 → Sep 28 2016

Other

Other	23rd IEEE International Conference on Image Processing, ICIP 2016
Country	United States
City	Phoenix
Period	9/25/16 → 9/28/16

Keywords

Aerial imagery
Bilateral symmetry
Hessian filter
Vehicle detection
Wavelet transform

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

Access to Document

10.1109/ICIP.2016.7533074

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Cite this

Ram, S., & Rodriguez, J. J. (2016). Vehicle detection in aerial images using multiscale structure enhancement and symmetry. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (Vol. 2016-August, pp. 3817-3821). [7533074] IEEE Computer Society. https://doi.org/10.1109/ICIP.2016.7533074

Ram, S & Rodriguez, JJ 2016, Vehicle detection in aerial images using multiscale structure enhancement and symmetry. in 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings. vol. 2016-August, 7533074, IEEE Computer Society, pp. 3817-3821, 23rd IEEE International Conference on Image Processing, ICIP 2016, Phoenix, United States, 9/25/16. https://doi.org/10.1109/ICIP.2016.7533074

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abstract = "Accurate detection and localization of vehicles in aerial images has a wide range of applications including urban planning, military reconnaissance, visual surveillance, and realtime traffic management. Automated detection of vehicles in aerial imagery is a challenging task, due to the density of vehicles on the road, the complexity of the surrounding environment in urban areas, and low spatial resolution of the image sensor array. We propose an automated method for detecting vehicles of varying sizes in low-resolution aerial imagery. First, we develop a new vehicle enhancement filter involving multiscale Hessian analysis. After thresholding, we refine the candidate vehicle detections based on analysis of bilateral symmetry. We show that our proposed method provides improved detection accuracy compared with existing vehicle detection algorithms for various low-resolution aerial images.",

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AB - Accurate detection and localization of vehicles in aerial images has a wide range of applications including urban planning, military reconnaissance, visual surveillance, and realtime traffic management. Automated detection of vehicles in aerial imagery is a challenging task, due to the density of vehicles on the road, the complexity of the surrounding environment in urban areas, and low spatial resolution of the image sensor array. We propose an automated method for detecting vehicles of varying sizes in low-resolution aerial imagery. First, we develop a new vehicle enhancement filter involving multiscale Hessian analysis. After thresholding, we refine the candidate vehicle detections based on analysis of bilateral symmetry. We show that our proposed method provides improved detection accuracy compared with existing vehicle detection algorithms for various low-resolution aerial images.

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