Vehicle detection in wide-area aerial imagery: cross-association of detection schemes with post-processings Online publication date: Sun, 18-Nov-2018
by Xin Gao
International Journal of Image Mining (IJIM), Vol. 3, No. 2, 2018
Abstract: Post-processing schemes are crucial for object detection algorithms to improve the performance of detection in wide-area aerial imagery. We select appropriate parameters for three algorithms (variational minimax optimisation (Saha and Ray, 2009), feature density estimation (Gleason et al., 2011) and Zheng's scheme by morphological filtering (Zheng et al., 2013)) to achieve the highest average F-score on random sample frames, and then follow the same procedure to implement five post-processing schemes on each algorithm. Two low-resolution aerial videos are used as our datasets to compare automatic detection results with the ground truth objects on each frame. The performance analysis of post-processing schemes on each algorithm are presented under two sets of evaluation metrics.
Online publication date: Sun, 18-Nov-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Image Mining (IJIM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com