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

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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.
Vehicle Detection in Aerial Video Based on Dynamic Event Signal
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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