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MPEG-4 AVC saliency map computation

机译:MPEG-4 AVC显着性图计算

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摘要

A saliency map provides information about the regions inside some visual content (image, video, ...) at which a human observer will spontaneously look at. For saliency maps computation, current research studies consider the uncompressed (pixel) representation of the visual content and extract various types of information (intensity, color, orientation, motion energy) which are then fusioned. This paper goes one step further and computes the saliency map directly from the MPEG-4 AVC stream syntax elements with minimal decoding operations. In this respect, an a-priori in-depth study on the MPEG-4 AVC syntax elements is first carried out so as to identify the entities appealing the visual attention. Secondly, the MPEG-4 AVC reference software is completed with software tools allowing the parsing of these elements and their subsequent usage in objective benchmarking experiments. This way, it is demonstrated that an MPEG-4 saliency map can be given by a combination of static saliency and motion maps. This saliency map is experimentally validated under a robust watermarking framework. When included in an m-QIM (multiple symbols Quantization Index Modulation) insertion method, PSNR average gains of 2.43 dB, 2.15dB, and 2.37 dB are obtained for data payload of 10, 20 and 30 watermarked blocks per Ⅰ frame, i.e. about 30, 60, and 90 bits/second, respectively. These quantitative results are obtained out of processing 2 hours of heterogeneous video content.
机译:显着性图提供有关一些视觉内容(图像,视频等)内部区域的信息,人类观察者将在这些区域内自发观看。对于显着图的计算,当前的研究考虑了视觉内容的未压缩(像素)表示形式,并提取了各种类型的信息(强度,颜色,方向,运动能),然后进行融合。本文进一步走了一步,并以最少的解码操作直接从MPEG-4 AVC流语法元素中计算出显着性图。在这方面,首先对MPEG-4 AVC语法元素进行了先验的深入研究,以识别吸引视觉注意力的实体。其次,MPEG-4 AVC参考软件是用软件工具完成的,该软件工具可以解析这些元素并随后在客观基准测试中使用。这样,证明了可以通过静态显着度和运动图的组合来给出MPEG-4显着度图。该显着性图在健壮的水印框架下进行了实验验证。当包含在m-QIM(多符号量化索引调制)插入方法中时,每Ⅰ帧有10、20和30个水印块的数据有效载荷,PSNR平均增益为2.43 dB,2.15dB和2.37 dB。 ,分别为60和90位/秒。这些量化结果是通过处理2小时的异构视频内容获得的。

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