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遮挡意识增强的行人检测方法OA

Pedestrian detection method with enhanced occlusion awareness

中文摘要英文摘要

不同程度的遮挡以及困难的遮挡关系建模是影响行人检测方法性能的关键因素.为应对这些问题,本文基于端到端检测框架提出一种遮挡意识增强的行人检测方法.首先,提出遮挡先验位置编码器,通过建模遮挡关系为多层解码器提供遮挡先验信息.其次,设计一种多尺度特征融合热力图预测器,精确捕捉目标中心点位置并增强感知目标能力,从而提升遮挡场景下的检测鲁棒性.最后,基于 CrowdHuman 和 CityPersons 数据集进行对比及消融实验,实验结果表明,本文方法可有效改善遮挡条件下的行人漏检和误检问题.

Occlusion of varying degrees and the challenges associated with modeling complex occlusion relationships are critical factors affecting pedestrian detection performance.To address these issues,an enhanced occlusion aware pedestrian detection method is proposed based on the end-to-end detection framework.First,an occlusion prior positional encoder is introduced to model occlusion relationships and provide occlusion prior information to the multi-layer decoder.Second,a multi-scale feature fusion heatmap predictor is designed to accurately capture the target center position and enhance target perception ability,thereby improving detection robustness in occluded scenes.Finally,comparative and ablation experiments are conducted on the CrowdHuman and CityPersons datasets.The experimental results demonstrate that the proposed method effectively alleviates the issues of missed detections and false positives under occlusion conditions.

杨晟;张家伟;韩少杰;张世辉

燕山大学 信息科学与工程学院,河北 秦皇岛 066004燕山大学 信息科学与工程学院,河北 秦皇岛 066004燕山大学 信息科学与工程学院,河北 秦皇岛 066004燕山大学 信息科学与工程学院,河北 秦皇岛 066004||燕山大学 河北省计算机虚拟技术与系统集成重点实验室,河北 秦皇岛 066004

信息技术与安全科学

模式识别遮挡检测目标检测遮挡意识增强Transformer

pattern recognitionocclusion detectionobject detectionocclusion aware enhancementTransformer

《燕山大学学报》 2026 (3)

258-266,9

国家自然科学基金资助项目(62476235)中央引导地方科技研发项目(216Z0301G)河北省自然科学基金资助项目(F2023203012)

10.3969/j.issn.1007-791X.2026.03.008

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