Video shot boundary detection (SBD) is a basic work of content-based video retrieval and analysis. Various SBD methods have been proposed; however, there exist limitations in the complexity of boundary detection process. In this paper, a simple yet efficient SBD method is proposed, and the aim here is to speed up the boundary detection and simplify the detection process without loss of detection recall and accuracy. In our proposed model, we mainly use a top-down zoom rule, the image color feature, and local descriptors and combine a kind of motion area extraction algorithm to achieve shot boundary detection. Firstly, we select candidate transition segments via color histogram and the speeded-up robust features. Then, we perform cut transition detection through uneven slice matching, pixel difference, and color histogram. Finally, we perform gradual transition detection by the motion area extraction, scale-invariant feature transform, and even slice matching. The experiment is evaluated on the TRECVid2001 and the TRECVid2007 video datasets, and the experimental results show that our proposed method improves the recall, accuracy, and the detection speed, compared with some other related SBD methods.

视频镜头边界检测（SBD）是基于内容的视频检索和分析的基础工作。已经提出了各种SBD方法。然而，边界检测过程的复杂性存在局限性。本文提出了一种简单而有效的SBD方法，其目的是在不损失检测召回率和准确性的情况下，加速边界检测并简化检测过程。在我们提出的模型中，我们主要使用自顶向下的缩放规则，图像颜色特征和局部描述符，并结合一种运动区域提取算法来实现镜头边界检测。首先，我们通过颜色直方图和加速的鲁棒特征选择候选过渡段。然后，我们通过不均匀切片匹配，像素差异和颜色直方图执行剪切过渡检测。最后，我们通过运动区域提取，尺度不变特征变换甚至切片匹配来执行逐步过渡检测。在TRECVid2001和TRECVid2007视频数据集上对实验进行了评估，实验结果表明，与其他一些相关的SBD方法相比，我们提出的方法提高了查全率，准确性和检测速度。