...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Optical engineering >Superpixel-based video saliency detection via the fusion of spatiotemporal saliency and temporal coherency
【24h】

Superpixel-based video saliency detection via the fusion of spatiotemporal saliency and temporal coherency

机译：通过时空显着性和时间相干性的融合实现基于超像素的视频显着性检测

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We advocate a model to effectively detect salient objects in various videos; the proposed framework [spatiotemporal saliency and coherency, (STSC)] consists of two modules, for capturing the spatiotemporal saliency and the temporal coherency information in the superpixel domain, respectively. We first extract the most straightforward gradient contrasts (such as the color gradient and motion gradient) as the low-level features to compute the high-level spatiotemporal gradient features, and the spatiotemporal saliency is obtained by computing the average weighted geodesic distance among these features. The temporal coherency, which is measured by the motion entropy, is then used to eliminate the false foreground superpixels that result from inaccurate optical flow and confusable appearance. Finally, the two discriminative video saliency indicators are combined to identify the salient regions. Extensive quantitative and qualitative experiments on four public datasets (FBMS, DAVIS, SegtrackV2, and ViSal dataset) demonstrate the superiority of the proposed method over the current state-of-the-art methods.
机译：我们提倡一种模型来有效检测各种视频中的显着物体；所提出的框架[时空显着性和相干性（STSC）]由两个模块组成，分别用于捕获超像素域中的时空显着性和时间相干性信息。我们首先提取最直接的梯度对比（例如颜色梯度和运动梯度）作为低级特征，以计算高级时空梯度特征，然后通过计算这些特征之间的平均加权测地距离来获得时空显着性。然后，通过运动熵来测量时间相干性，以消除由于光流不准确和外观混乱而导致的虚假前景超像素。最后，将两个判别式视频显着性指标组合起来以标识显着区域。在四个公共数据集（FBMS，DAVIS，SegtrackV2和ViSal数据集）上进行的大量定量和定性实验证明，该方法优于当前的最新方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号