FASA: Fast, Accurate, and Size-Aware Salient Object Detection
FASA: Fast, Accurate, and Size-Aware Salient Object Detection
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DOI：
10.1007/978-3-319-16811-1_34
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发表时间：
2014-11
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影响因子：
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通讯作者：
Gökhan Yildirim;S. Süsstrunk
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文献类型：
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作者：
Gökhan Yildirim;S. Süsstrunk
快速而准确的显着对象检测器对于各种图像处理和计算机视觉应用（例如自适应压缩和对象分割）非常重要。还希望有一个能够了解显着物体的位置和尺寸的检测器。在本文中，我们提出了一种快速、准确且尺寸感知的显着目标检测方法。为了有效计算，我们量化图像颜色并估计量化颜色的空间位置和大小。然后，我们将这些值输入统计模型以获得显着性概率。为了估计最终的显着性，该概率与全局颜色对比度度量相结合。我们在两个公共数据集上测试我们的方法，并表明我们的方法显着优于快速的最先进的方法。此外，它具有可比的性能，并且比最先进的精确方法快一个数量级。我们通过实时处理高清视频来展示我们的算法的潜力。
Fast and accurate salient-object detectors are important for various image processing and computer vision applications, such as adaptive compression and object segmentation. It is also desirable to have a detector that is aware of the position and the size of the salient objects. In this paper, we propose a salient-object detection method that is fast, accurate, and size-aware. For efficient computation, we quantize the image colors and estimate the spatial positions and sizes of the quantized colors. We then feed these values into a statistical model to obtain a probability of saliency. In order to estimate the final saliency, this probability is combined with a global color contrast measure. We test our method on two public datasets and show that our method significantly outperforms the fast state-of-the-art methods. In addition, it has comparable performance and is an order of magnitude faster than the accurate state-of-the-art methods. We exhibit the potential of our algorithm by processing a high-definition video in real time.