中心偏置增强视觉显著性检测方法

A. Diana Andrushia, R. Thangarajan
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引用次数: 1

摘要

由于多媒体技术的进步,图像和视频在日常生活中扮演着重要的角色。人类是如何看待图像的?视觉注意的计算模型用于许多计算机视觉任务,如图像分割、物体识别、图像理解等。该方法旨在利用中心偏差和前注意特征构建视觉显著性模型。介绍了自底向上的视觉显著性模型。中心偏差的影响是该方法的关键机理。采用高斯差分滤波(DOG)和高斯包络函数对图像中的显著目标进行识别。实验结果与现有的五种方法进行了比较。基准数据库用于获取性能指标。利用受试者工作特征(Receiver Operating characteristic, ROC)、精密度、召回率和f-measure来分析该方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Center bias enhanced visual saliency detection method
Due to the advancement in multimedia technology, the images and videos play a major role in day today life. How the humans are looking into the image? The computational models of visual attention used in many of the computer vision tasks such as image segmentation, object recognition, image understanding, etc. The proposed method aims to construct visual saliency model with the help of the center bias and pre-attentive features. The bottom-up visual saliency model is introduced. Influence of Center bias is the key mechanism of the proposed method. Difference of Gaussian (DOG) filter and gaussian envelope function are used to identify the salient objects of an image. The experimental results of the proposed method compared with five state-of-art-methods. The benchmark database is used to obtain the performance metrics. Receiver Operating Characteristics (ROC), precision, recall and f-measure are found to analyze the performance of the proposed method.
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