Efficient Face Detection in the Fisheye Image Domain
Journal
IEEE Transactions on Image Processing
Journal Volume
30
Pages
5641-5651
Date Issued
2021
Author(s)
Yang C.-Y
Abstract
Significant progress has been made for face detection from normal images in recent years; however, accurate and fast face detection from fisheye images remains a challenging issue because of serious fisheye distortion in the peripheral region of the image. To improve face detection accuracy, we propose a light-weight location-aware network to distinguish the peripheral region from the central region in the feature learning stage. To match the face detector, the shape and scale of the anchor (bounding box) is made location dependent. The overall face detection system performs directly in the fisheye image domain without rectification and calibration and hence is agnostic of the fisheye projection parameters. Experiments on Wider-360 and real-world fisheye images using a single CPU core indeed show that our method is superior to the state-of-the-art real-time face detector RFB Net. ? 1992-2012 IEEE.
Subjects
face detection
Fisheye camera
fisheye distortion
image rectification
Image processing
Mathematical models
Detection accuracy
Efficient faces
Face detection system
Feature learning
Fisheye images
Location dependents
Peripheral regions
State of the art
Face recognition
Agnostic
article
calibration
human
learning
Type
journal article