一种改进YOLOv3的手势识别算法
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河北科技大学信息科学与工程学院

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TP3

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A gesture recognition algorithm based on improved yolov3
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1.School of Information Science and Engineering,Hebei University of Science and Technology,Shijiazhuang Hebei 050000;2.China

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    摘要:

    针对YOLOv3算法在手势识别中存在识别精度低及易受光照条件影响等问题,提出了一种基于改进的YOLOv3手势识别算法。首先在原来三个检测尺度上新增加一个更小的检测尺度以提高对小目标的检测能力。其次采用损失代替均方差损失,以提高预测框准确率和回归速度。同时使用自适应的平衡参数和聚焦参数改进Focal损失函数并加入到总损失函数,用来缓解训练样本的不均衡问题。实验结果表明,该算法应用于手势检测中,mAP指标达到90.38%,相较于改进前提升了6.62%,同时FPS提升了近2倍。

    Abstract:

    Aiming at the problems of low recognition accuracy and easy to be affected by illumination conditions in gesture recognition based on yolov3 algorithm, a gesture recognition algorithm based on improved yolov3 is proposed. Firstly, a smaller detection scale is added to the original three detection scales to improve the detection ability of small targets. Secondly, the mean square error loss was replaced by loss to improve the accuracy of prediction frame and regression speed. At the same time, the adaptive balance parameter and focus parameter are used to improve the focal loss function and add it to the total loss function to alleviate the imbalance problem of training samples. The experimental results show that the map index reaches 90.38%, which is 6.62% higher than that before the improvement, and FPS is improved nearly twice.

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  • 收稿日期:2020-09-28
  • 最后修改日期:2020-09-28
  • 录用日期:2022-04-26
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