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) |
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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 | |
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 |
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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