首页|基于仿生动态信号的航拍车辆检测算法

基于仿生动态信号的航拍车辆检测算法

Vehicle Detection in Aerial Video Based on Dynamic Event Signal

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现有主流航拍车辆检测算法均针对传统视频设计,但传统视频数据量巨大且存在信息冗余,这些缺点导致现有算法过于复杂且计算量大,运行效率低.提出基于仿生动态信号的航拍车辆检测算法,将整体检测系统拆分为候选目标定位模块与 目标检测模块.候选目标定位模块以单个动态事件为输入,结合一定时空邻域内的局部动态事件群,快速定位候选目标.目标检测模块对传统ResNet结构进行改进,提出加入特征融合的M-ResNet以保护浅层特征.此外,制作了时长为25 s,含有295 633 872个动态事件的车辆事件数据集,通过该数据集验证该文提出算法可快速精准地检测出场景内的车辆.
In this paper,an aerial vehicle detection algorithm based on the dynamic event signal is proposed by split-ting the detection system into a candidate target positioning module and a target detection module.The candidate target positioning module takes one single dynamic event as input,combining events within a certain spatial-temporal neighbor-hood to quickly locate candidate targets.Moreover,M-ResNet with feature fusion is proposed in target detection module to protect shallow features.Finally,this paper produces a vehicle event data set with a duration of 25 seconds and 295,633,872 dynamic events,and verifies that the algorithm proposed in this paper can quickly and accurately detect vehi-cles in the scene through this data set.

dynamic event signalobject detectionaerial videoconvolutional neural network

陈佳媛、王斌

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上海大学通信与信息工程学院,上海 200444

仿生动态信号 目标检测 航拍视频 卷积神经网络

2024

工业控制计算机
中国计算机学会工业控制计算机专业委员会 江苏省计算技术研究所有限责任公司

工业控制计算机

影响因子:0.258
ISSN:1001-182X
年,卷(期):2024.37(2)
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