Open AccessImage Processing Framework for Face Detection and Face Swapping in Group Photo Refinement
Author(s) -
Min Zhang,
Yuxuan Huang,
Yanze Wang,
Jian Xue
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1345/2/022009
Subject(s) - computer science , set (abstract data type) , face (sociological concept) , face detection , artificial intelligence , process (computing) , group (periodic table) , image (mathematics) , human–computer interaction , facial recognition system , computer vision , feature extraction , social science , chemistry , organic chemistry , sociology , programming language , operating system
As the trend of big data and increasingly widespread social networking sites, people are enjoying sharing their daily lives by displaying selfies or group photos online, creating large amount of data, which indicates great effort that online servers or applications may have to spend to edit and process personal photographs. However, human face processing requires elaborate skill that is time-consuming if is operated manually. while image processing, as a crucial research area in fields of AI (Artificial Intelligence), plays its indispensable role of setting us free from these repetitive routines. In order to solve existing problems, this paper proposes a relatively reliable and complete framework to refine photos of human facial expressions of emotions among a set of group photos both partially and wholly based on existing techniques of face detection and face swapping. In addition, this framework also involves procedures of extraction of face features relied on Dlib library. Finally, a set of experimental results and relevant statics are displayed to indicate some future works that have to be carried out.