Title
Faceless Identification Based On Temporal Strips
Abstract
This paper first presents a novel approach for modelling facial features, Local Directional Texture (LDT), which exploits the unique directional information in image textures for the problem of face recognition. A variant of LDT with privacy-preserving temporal strips (TS) is then considered to achieve faceless recognition with a higher degree of privacy while maintaining high accuracy. The TS uses two strips of pixel blocks from the temporal planes, XT and YT, for face recognition. By removing the reliance on spatial context (i.e., XY plane) for this task, the proposed method withholds facial appearance information from public view, where only one-dimensional temporal information that varies across time are extracted for recognition. Thus, privacy is assured, yet without impeding the facial recognition task which is vital for many security applications such as street surveillance and perimeter access control. To validate the reliability of the proposed method, experiments were carried out using the Honda/UCSD, CK+, CAS(ME)(2)and CASME II databases. The proposed method achieved a recognition rate of 98.26% in the standard video-based face recognition database, Honda/UCSD. It also offers a 81.92% reduction in the dimension length required for storing the extracted features, in contrast to the conventional LBP-TOP.
Year
DOI
Venue
2021
10.1007/s11042-020-09391-7
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Facial recognition, Privacy-preserving, Temporal features, Local directional textures, Local binary pattern (LBP), Partial facial features
Journal
80
Issue
ISSN
Citations 
1
1380-7501
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Shu-Min Leong100.34
Raphaël C.-W. Phan201.01
Vishnu Monn Baskaran3248.12
Chee-Pun Ooi422.05