An On-Road Vehicle Detection Method for High-Resolution Aerial Images Based on Local and Global Structure Learning

2017 ◽  
Vol 14 (8) ◽  
pp. 1198-1202 ◽  
Author(s):  
Jiaxing Zhang ◽  
Chao Tao ◽  
Zhengrong Zou
Keyword(s):  
High Resolution ◽  
Structure Learning ◽  
Detection Method ◽  
Vehicle Detection ◽  
Global Structure ◽  
Aerial Images ◽  
Road Vehicle

scholarly journals Vehicle Detection in Very-High-Resolution Remote Sensing Images Based on an Anchor-Free Detection Model with a More Precise Foveal Area

2021 ◽  
Vol 10 (8) ◽  
pp. 549
Author(s):  
Xungen Li ◽  
Feifei Men ◽  
Shuaishuai Lv ◽  
Xiao Jiang ◽  
Mian Pan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Target Detection ◽  
Detection Method ◽  
Vehicle Detection ◽  
Aerial Images ◽  
Background Information ◽  
Remote Sensing Images ◽  
Feature Pyramid ◽  
Very High

Vehicle detection in aerial images is a challenging task. The complexity of the background information and the redundancy of the detection area are the main obstacles that limit the successful operation of vehicle detection based on anchors in very-high-resolution (VHR) remote sensing images. In this paper, an anchor-free target detection method is proposed to solve the problems above. First, a multi-attention feature pyramid network (MA-FPN) was designed to address the influence of noise and background information on vehicle target detection by fusing attention information in the feature pyramid network (FPN) structure. Second, a more precise foveal area (MPFA) is proposed to provide better ground truth for the anchor-free method by determining a more accurate positive sample selection area. The proposed anchor-free model with MA-FPN and MPFA can predict vehicles accurately and quickly in VHR remote sensing images through direct regression and predict the pixels in the feature map. A detailed evaluation based on remote sensing image (RSI) and vehicle detection in aerial imagery (VEDAI) data sets for vehicle detection shows that our detection method performs well, the network is simple, and the detection is fast.

Robust Vehicle Detection in High-Resolution Aerial Images with Imbalanced Data

2021 ◽  
pp. 1-1
Author(s):  
Xianghui Li ◽  
Xinde Li ◽  
Zhijun Li ◽  
Xinran Xiong ◽  
Mohammad Omar Khyam ◽  
...  
Keyword(s):  
High Resolution ◽  
Imbalanced Data ◽  
Vehicle Detection ◽  
Aerial Images

Vehicle Detection in High-Resolution Aerial Images via Sparse Representation and Superpixels

2016 ◽  
Vol 54 (1) ◽  
pp. 103-116 ◽  
Author(s):  
Ziyi Chen ◽  
Cheng Wang ◽  
Chenglu Wen ◽  
Xiuhua Teng ◽  
Yiping Chen ◽  
...  
Keyword(s):  
High Resolution ◽  
Sparse Representation ◽  
Vehicle Detection ◽  
Aerial Images

Vehicle detection from high-resolution aerial images based on superpixel and color name features

2016 ◽  
Author(s):  
Ziyi Chen ◽  
Liujuan Cao ◽  
Zang Yu ◽  
Yiping Chen ◽  
Cheng Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Vehicle Detection ◽  
Aerial Images ◽  
Color Name
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