Hardware-aware motion estimation via low-resolution motion hints

Pao-Sheng Chouy, Nuwan S. Ferdinand, Ihab Amerz, S. Draper
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Abstract

This paper presents an algorithm that achieves high quality video compression with low memory bandwidth of reference frame data and latency due to computation in motion estimation for screen content. Efficiency is attained by content-adaptive placement of the search windows within the reference frames. In our scheme, the center location of the search window is decided by k most prominent motion vectors under a low resolution pre-analysis of the video content. The algorithm leverages the motion hints obtained during pre-analysis to improve encoding efficiency, while keeping implementation complexity and power budget in an acceptable range. Experimental results show that without increasing the size of the search window when large motion is present, it is still possible to capture the motion and achieve within 1.3 dB BDPSNR compared to the HEVC Test Model HM through smart placement of the search window.
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基于低分辨率运动提示的硬件感知运动估计
本文提出了一种基于参考帧数据的低内存带宽和由于计算屏幕内容的运动估计而导致的延迟来实现高质量视频压缩的算法。效率是通过在参考框架内自适应内容的搜索窗口放置来实现的。在我们的方案中,在视频内容的低分辨率预分析下,搜索窗口的中心位置由k个最突出的运动向量决定。该算法利用预分析过程中获得的运动提示来提高编码效率,同时将实现复杂度和功耗预算保持在可接受的范围内。实验结果表明,在不增加搜索窗口大小的情况下,与HEVC测试模型HM相比,通过智能放置搜索窗口,仍然可以捕获运动并实现1.3 dB的BDPSNR。
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