Saliency detection is one of the most challenging problems in image analysis and computer vision. Many approaches propose different architectures based on the psychological and biological properties of the human visual attention system. However, there is still no abstract framework that summarizes the existing methods. In this paper, we offered a general framework for saliency models, which consists of five main steps: pre-processing, feature extraction, saliency map generation, saliency map combination, and post-processing. Also, we study different saliency models containing each level and compare their performance. This framework helps researchers to have a comprehensive view of studying new methods.
翻译:色素检测是图像分析和计算机视觉中最具挑战性的问题之一,许多方法都根据人类视觉关注系统的心理和生物特性提出不同的结构,然而,目前还没有总结现有方法的抽象框架,在本文件中,我们为突出模型提供了一个总体框架,其中包括五个主要步骤:预处理、特征提取、突出的地图生成、突出的地图组合和后处理。此外,我们还研究包含各个层次的不同突出模型并比较其性能。这个框架有助于研究人员全面了解研究新方法的情况。