Can you tell a face from a HEVC bitstream?

被引:9
作者
Alvar, Saeed Ranjbar [1 ]
Choi, Hyomin [1 ]
Bajic, Ivan V. [1 ]
机构
[1] Simon Fraser Univ, Sch Engn Sci, Burnaby, BC, Canada
来源
IEEE 1ST CONFERENCE ON MULTIMEDIA INFORMATION PROCESSING AND RETRIEVAL (MIPR 2018) | 2018年
关键词
face detection; HEVC; deep learning; convolutional neural network;
D O I
10.1109/MIPR.2018.00060
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
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.
引用
收藏
页码:257 / 261
页数:5
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