Efficient Models for Real-time Person Segmentation on Mobile Phones

被引:3
作者
Strohmayer, Julian [1 ]
Knapp, Jakob [1 ]
Kampel, Martin [1 ]
机构
[1] TU Wien, Comp Vis Lab, Vienna, Austria
来源
29TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2021) | 2021年
关键词
real time; person segmentation; mobile phone; PORTRAIT SEGMENTATION;
D O I
10.23919/EUSIPCO54536.2021.9616237
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Despite constantly evolving mobile hardware, real-time person segmentation on mobile phones is challenging due to the limited computational resources. To address this problem, we introduce a novel UNet-like network architecture based on MobileNetV3, which enables the segmentation of persons in images and videos on mobile phones. Our model, which is not limited to a specific shot type, outperforms specialized models in their respective domains and runs with 35 fps on a Google Pixel 4 mobile phone. Moreover, we demonstrate how the segmentation accuracy can be further improved by exploiting the temporal coherence of consecutive frames in videos.
引用
收藏
页码:651 / 655
页数:5
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