Paper Info
Title
Real-world Mapping of Gaze Fixations Using Instance Segmentation for Road Construction Safety Applications.
Abstract
Research studies have shown that a large proportion of hazards remain unrecognized, which expose construction workers to unanticipated safety risks. Recent studies have also found that a strong correlation exists between viewing patterns of workers, captured using eye-tracking devices, and their hazard recognition performance. Therefore, it is important to analyze the viewing patterns of workers to gain a better understanding of their hazard recognition performance. This paper proposes a method that can automatically map the gaze fixations collected using a wearable eye-tracker to the predefined areas of interests. The proposed method detects these areas or objects (i.e., hazards) of interests through a computer vision-based segmentation technique and transfer learning. The mapped fixation data is then used to analyze the viewing behaviors of workers and compute their attention distribution. The proposed method is implemented on an under construction road as a case study to evaluate the performance of the proposed method.
Year
Venue
DocType
2019
arXiv: Computer Vision and Pattern Recognition
Journal
Volume
Citations 
PageRank 
abs/1901.11078
0
0.34
References 
Authors
12
5
Name
Order
Citations
PageRank
Idris Jeelani100.68
Khashayar Asadi220.84
Hariharan Ramshankar320.84
Kevin K. Han442.22
Alex Albert500.68