计算机科学 ›› 2019, Vol. 46 ›› Issue (2): 249-254.doi: 10.11896/j.issn.1002-137X.2019.02.038
盛雷, 卫志华, 张鹏宇
SHENG Lei, WEI Zhi-hua, ZHANG Peng-yu
摘要： 目标检测是计算机视觉领域的热门研究课题,是视频内容分析的基础。文中提出了一种基于图像多源特征后融合的分层目标检测算法。在该算法中,使用多级决策的思想对目标检测任务进行粗细两个粒度的划分。在粗粒度层面,先使用HOG特征对图像进行分类,根据分类器的置信度分数,将测试图像分为正例、负例和不确定例。在细粒度层面,使用多种视觉特征以及多种核函数后融合的方法对不确定域中的图像做进一步分类。在同一数据集上设置了3组对比实验。实验结果表明,所提算法在各个评价指标上都有出色的表现,且在实际视频的目标检测中的效果优于Faster-RCNN。
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