计算机工程2025，Vol.51Issue(2)：65-77,13.DOI:10.19678/j.issn.1000-3428.0069079
基于分区的高效视频目标检测
Efficient Video Object Detection Based on Partitioning
摘要
Abstract
To address the challenge of balancing accuracy requirements and computational costs of object detection using deep neural networks for video analysis tasks,existing methods predominantly use entire video frames as units for computational resource allocation.To minimize computational costs while ensuring accuracy,these methods allocate more resources to frames with high information values,whereas frames with low information values receive less or no resource allocation.However,this strategy overlooks the uneven distribution of objects of interest within each video frame.This can lead to unnecessary computational overhead when excessive resources are allocated to highly informative regions within a small portion of a full-frame image.To address this issue,an efficient video object detection method based on partitioning is proposed.After partitioning the video frames,the features of the objects in each partition are extracted and processed rapidly.A configuration mapping analyzer is employed to map the detection configurations for each partition,thus satisfying the accuracy requirements while minimizing detection costs.Partitions with the same detection configuration are then concatenated for detection,further reducing the overall detection costs.Finally,corrective measures are implemented to address edge object fragmentation issues caused by partitioning,which lead to a decline in detection accuracy.The experimental results demonstrate that under the premise of meeting the accuracy requirements,this method significantly reduces computational costs,achieving a maximum saving of 90.84％.In situations with similar costs,the method averages a 10.48％-23.13％improvement in accuracy.This approach achieves efficient video object detection and exhibits superior adaptability across diverse scenarios.关键词
视频分析/深度神经网络/目标检测/分区/配置映射分析器/拼接检测Key words
video analysis/deep neural networks/object detection/partitioning/configuration mapping analyzer/concatenation detection分类
计算机与自动化引用本文复制引用
黄舒怡,谭光..基于分区的高效视频目标检测[J].计算机工程,2025,51(2):65-77,13.基金项目
国家自然科学基金面上项目(62372488). （62372488）
