Region-of-Interest Based Conversational HEVC Coding with Hierarchical Perception Model of Face

In this paper, we propose a region-of-interest (ROI) based HEVC coding approach for conversational videos, with a novel hierarchical perception model of face (HP model), to improve the perceived visual quality of state-of-the-art HEVC standard. In contrast to the previous ROI-based video coding approaches, this novel HP model allows the unequal importance of facial features (e. g., the eyes and mouth) within the facial region, by generating a pixel-wise weight map. Benefitting from such a perception model, the adaptive coding tree unit (CTU) partition structure is developed to alleviate the encoding complexity of HEVC, without any degradation of the visual quality in facial regions, especially in the regions of facial features. Subsequently, for the rate control in HEVC a weight-based unified rate-quantization (URQ) scheme, instead of the conventional pixel-based URQ scheme, is proposed to adaptively adjust the value of quantization parameter (QP). Such an adaptive adjustment of QPs is capable of allocating more bits to the face/facial features with respect to our HP model, and as a result, the visual quality of face, in particular facial features, can be enhanced for conversational HEVC coding. Finally, the experimental results show that the perceived visual quality of our approach is greatly improved, with even less encoding time, for conversational video coding on the HEVC platform.

在本文中，我们针对会话视频提出了一种基于感兴趣区域（ROI）的高效视频编码（HEVC）方法，该方法采用一种新颖的人脸分层感知模型（HP模型），以提高最先进的HEVC标准的感知视觉质量。与之前基于ROI的视频编码方法不同，这种新颖的HP模型通过生成逐像素权重图，考虑到面部区域内面部特征（例如眼睛和嘴巴）的不同重要性。受益于这种感知模型，开发了自适应编码树单元（CTU）划分结构，以减轻HEVC的编码复杂度，同时不会降低面部区域（尤其是面部特征区域）的视觉质量。随后，针对HEVC中的码率控制，提出了一种基于权重的统一码率 - 量化（URQ）方案，以替代传统的基于像素的URQ方案，从而自适应地调整量化参数（QP）的值。这种对QP的自适应调整能够根据我们的HP模型为面部/面部特征分配更多比特，因此，对于会话HEVC编码，可以提高面部（尤其是面部特征）的视觉质量。最后，实验结果表明，在HEVC平台上进行会话视频编码时，我们的方法在感知视觉质量上有很大提高，并且编码时间更短。