【24h】

Can You Tell a Face from a HEVC Bitstream?

机译:您能从HEVC比特流中分辨出面孔吗?

获取原文
获取原文并翻译 | 示例

摘要

Image and video analytics are being increasingly used on a massive scale. Not only is the amount of data growing, but the complexity of the data processing pipelines is also increasing, thereby exacerbating the problem. It is becoming increasingly important to save computational resources wherever possible. We focus on one of the poster problems of visual analytics - face detection - and approach the issue of reducing the computation by asking: Is it possible to detect a face without full image reconstruction from the High Efficiency Video Coding (HEVC) bitstream? We demonstrate that this is indeed possible, with accuracy comparable to conventional face detection, by training a Convolutional Neural Network on the output of the HEVC entropy decoder.
机译:图像和视频分析越来越广泛地被使用。不仅数据量在增加,而且数据处理管道的复杂性也在增加,从而加剧了该问题。尽可能节省计算资源变得越来越重要。我们专注于视觉分析的先发问题之一-人脸检测-并提出以下问题来解决减少计算的问题:是否可以从高效视频编码(HEVC)比特流中检测到没有完整图像重建的人脸?我们证明,通过在HEVC熵解码器的输出上训练卷积神经网络,以与传统人脸检测相当的准确性确实可以实现这一点。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号