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A Novel Matching Operator for Visual Object Tracking

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Abstract

Visual object tracking is among the extremely attractive topics in various vision system applications. The appearance of the target object often drastically changes over time due to complicated attributes such as motion blur and fast motion; accordingly object tracking is a challenging issue. Over the past few years, Siamese architecture has been satisfactorily employed in object tracking because of its great accuracy and robustness. In this paper, a new matching operator for determining the similarity between the template image and search region to locate the state of the object is introduced. The matching operator is a weighted sum of depth-wise cosine similarity and depth-wise cross-correlation. For computing cosine similarity in each block, extracted features from the backbone architecture are divided into column vectors in each channel. The similarity is calculated in corresponding columns. Then, the max-pooling operation is applied to similarity values, and the maximum value is assigned to the center of the block. Finally, the combination of cosine similarity and cross-correlation in each channel is used. The results on OTB-100 demonstrate that the proposed tracker acquires promising prediction performance concerning the state-of-the-art tracking techniques in terms of motion blur, fast motion, and also out-of-view attributes.

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Authors and Affiliations

  1. Computer Engineering Department, Yazd University, Yazd, Iran

    Soolmaz Abbasi & Mehdi Rezaeian

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  1. Soolmaz Abbasi
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  2. Mehdi Rezaeian
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Contributions

Soolmaz Abbasi and Mehdi Rezaeian conceived of the presented idea. Soolmaz Abbasi developed the theory and performed the computations and experiments. Mehdi Rezaeian encouraged Soolmaz Abbasi to investigate the superiority of cosine similarity against fast motion and motion blur attributes and supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.

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Correspondence to Mehdi Rezaeian.

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Abbasi, S., Rezaeian, M. A Novel Matching Operator for Visual Object Tracking. Neural Process Lett 55, 9065–9084 (2023). https://doi.org/10.1007/s11063-023-11192-6

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