基于差分特征注意力机制的无锚框多光谱行人检测算法

Anchor free multispectral pedestrian detection algorithm based on differential feature attention mechanism

针对多光谱行人检测系统存在特征融合质量低、模型超参数多且锚框匹配算法复杂等问题,提出了一种基于差分特征注意力机制的无锚框多光谱行人检测算法。该算法首先采用差分特征感知融合方法挖掘多模态特征间的互补信息来优化通道特征;然后利用具有高效无锚框机制的CenterNet检测框架大大降低了模型计算复杂度,从而提升检测速度;最后引入差分特征注意力机制,改善特征融合质量,进一步提升检测精度。在KAIST、CVC14和FLIR这3个公开数据集上的实验结果表明,提出的算法和其他先进方法相比,能够同时有效提升检测精度和速度,具有较好的实际应用前景。

Multispectral pedestrian detection system suffers with low feature fusion quality,high quantity of model hy-per-parameters and complex anchor matching algorithm.To deal with these problems,an anchor free multispectral pede-strian detection algorithm based on differential feature attention mechanism was proposed.Firstly,differential modality aware fusion was used to obtain the complementary information between different modalities to optimize the channel features.Secondly,the CenterNet detection framework with anchor free mechanism was adopted to greatly reduce the computational complexity of the model and thus improve the detection speed.Finally,differential feature guided attention mechanism was introduced to improve the quality of feature fusion and further enhance the detection accuracy.Experi-mental results on three open datasets,KAIST,CVC14 and FLIR,show that the proposed algorithm can effectively improve the detection accuracy and speed compared with the current advanced methods,and has a good practical application prospect.