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Face-Tracking and Coding for Video Compression

机译:人脸跟踪和视频压缩编码

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While computing power and transmission bandwidth have both been steadily increasing over the last few years, bandwidth rather than processing power remains the primary bottleneck for many complex multimedia applications involving communication. Current video coding algorithms use intelligent encoding to yield higher compression ratios at the cost of additional computing requirements for encoding and decoding. The use of techniques from the fields of computer vision and robotics such as object recognition, scene interpretation, and tracking can further improve compression ratios as well as provide additional information about the video sequence being transmitted. We used a new face tracking system developed in the robotics area to normalize a video sequence to centered images of the face. The face-tracking allowed us to implement a compression scheme based on Principal Component Analysis (PCA), which we call Orthonormal Basis Coding (OBC). We designed and implemented the face tracker and video codecs entirely in software. Our current implementation of OBC operates on recorded video sequences, making it appropriate for applications such as video email.
机译:在过去几年中,尽管计算能力和传输带宽都在稳步增长,但是带宽(而不是处理能力)仍然是涉及通信的许多复杂多媒体应用程序的主要瓶颈。当前的视频编码算法使用智能编码来产生更高的压缩率,但以编码和解码所需的额外计算需求为代价。使用计算机视觉和机器人技术领域的技术(例如对象识别,场景解释和跟踪)可以进一步提高压缩率,并提供有关正在传输的视频序列的其他信息。我们使用了在机器人技术领域开发的新的面部跟踪系统,将视频序列标准化为面部中心图像。面部跟踪使我们能够基于主成分分析(PCA)实施压缩方案,我们将其称为正交基础编码(OBC)。我们完全通过软件设计和实现了面部跟踪器和视频编解码器。我们当前对OBC的实现对记录的视频序列进行操作,使其适合视频电子邮件等应用程序。

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