Single Object Tracking Algorithm Based on Multilayer Feature Embedding

doi:10.12382/bgxb.2024.0062

Abstract

Abstract:

The existing visual object tracking methods often face the challenge of tracking failure when dealing with complex backgrounds or drastic appearance changes due to relying solely on the initial frame’s single appearance feature.To address this issue,a single object tracking algorithm based on multilayer feature embedding is proposed.To enhance the discriminability of the target’s appearance,a sparse embedded attention encoder is employed to embed the appearance features with high instance distinctiveness.Additionally,an category feature aggregation encoder is utilized to embed the target’s category information,maintaining the compactness within the class when the appearance changes occur.Simultaneously,the predicted historical frame tracking box coordinates are transformed into the embedded target motion trajectory features,providing the tracking algorithm with high-confidence temporal context features.Experimental results demonstrate that the proposed algorithm achieves a success rate of 71.4% and an accuracy of 92.6% in the OTB100 benchmark test.Moreover,it exhibits robust performance on three large-scale public datasets,namely GOT-10K,LaSOT,and TrackingNet,with success rates reaching 64.9%,72.0%,and 78.7%,respectively.The proposed algorithm effectively overcomes the limitations of the existing tracking algorithms,and has the enhanced tracking accuracy and robustness.

Key words: object tracking, sparse embedded attention encoder, category feature aggregation encoder, motion feature embedding

CLC Number:

TP391

CAI Hua, ZHOU Hongce, FU Qiang, ZHAO Yiwu. Single Object Tracking Algorithm Based on Multilayer Feature Embedding[J]. Acta Armamentarii, 2025, 46(3): 240062-.

Figures/Tables 14

References 9

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序号	搜索区域	原始特征	实例增强特征	类别聚合特征
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序号	搜索区域	原始特征	实例增强特征	类别聚合特征
1
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视频序列	不同算法的跟踪结果
自行车
鸟
盒子
女孩
液体

视频序列	不同算法的跟踪结果
自行车
鸟
盒子
女孩
液体

模型编号	稀疏内嵌注意力编码器	类间特征聚合编码器	运动特征嵌入	成功率	精度
MFET(0)	√			0.671	0.887
MFET(1)	√	√		0.694	0.900
MFET(2)	√		√	0.692	0.897
MFET(3)	√	√	√	0.714	0.926