A Joint Compression Scheme of Video Feature Descriptors and Visual Content

A Joint Compression Scheme of Video Feature Descriptors and Visual Content
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视频特征描述符和视觉内容的联合压缩方案

DOI:
10.1109/tip.2016.2629447
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发表时间:
2017-02
影响因子:
10.6
通讯作者:
Gao Wen
Gao Wen
中科院分区:
计算机科学1区
文献类型:
--
作者:
Zhang Xiang;Ma Siwei;Wang Shiqi;Zhang Xinfeng;Sun Huifang;Gao Wen

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近年来,由于在带宽有限的网络上移动的视觉检索的需求迅速增长,视觉特征描述符的高效压缩成为一个活跃的话题。然而,由于缺乏必要的视觉内容,仅传输这些特征描述符可能会在很大程度上限制其应用规模。为了促进特征描述符的广泛传播,非常需要联合压缩特征描述符和视觉内容的混合框架。在本文中,这样的内容加特征的编码方案进行了研究,旨在塑造下一代的视频压缩系统的视觉检索,其中的高效率的编码的特征描述符和视觉内容可以通过利用彼此之间的相互作用。一方面,视觉特征描述符可以利用压缩视频流中的结构和运动信息来实现简洁高效的表示。为了优化检索性能,提出了一种新的率精度优化技术,以准确地估计检索性能下降的特征编码。另一方面,通过应用基于特征匹配的仿射运动补偿,可以利用已经压缩的特征数据来进一步提高视频编码效率。大量的模拟结果表明,所提出的联合压缩框架可以提供显着的比特率降低表示特征描述符和视频帧,同时保持最先进的视觉检索性能。
High-efficiency compression of visual feature descriptors has recently emerged as an active topic due to the rapidly increasing demand in mobile visual retrieval over bandwidth-limited networks. However, transmitting only those feature descriptors may largely restrict its application scale due to the lack of necessary visual content. To facilitate the wide spread of feature descriptors, a hybrid framework of jointly compressing the feature descriptors and visual content is highly desirable. In this paper, such a content-plus-feature coding scheme is investigated, aiming to shape the next generation of video compression system toward visual retrieval, where the high-efficiency coding of both feature descriptors and visual content can be achieved by exploiting the interactions between each other. On the one hand, visual feature descriptors can achieve compact and efficient representation by taking advantages of the structure and motion information in the compressed video stream. To optimize the retrieval performance, a novel rate-accuracy optimization technique is proposed to accurately estimate the retrieval performance degradation in feature coding. On the other hand, the already compressed feature data can be utilized to further improve the video coding efficiency by applying feature matching-based affine motion compensation. Extensive simulations have shown that the proposed joint compression framework can offer significant bitrate reduction in representing both feature descriptors and video frames, while simultaneously maintaining the state-of-the-art visual retrieval performance.
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