Paper Info
Title
Object of Fixation Estimation by Joint Analysis of Gaze and Object Dynamics.
Abstract
Determining object of fixation is an important factor in many application of intelligent vehicles including driver’s situational awareness estimation. The objective of this work is to infer object of fixation given fixation is occurring. We propose a system architecture that identifies object tracks in the scene, derives object characteristics independent of and jointly with gaze behavior, and utilizes a spatio-temporal sensitive machine learning framework to estimate the likelihood of an object being the object of fixation. Performance evaluation is conducted on a dataset of on-road driving, centered around urban intersections, with manual annotations of object of fixation. Our proposed system can achieve up to 83% average precision accuracy when compared to baseline of 78%.Furthermore, comparing the effects of different combinations of object characteristics on precision and recall accuracy show promising insights on factors affecting reliable estimation of object of fixation.
Year
Venue
Field
2018
Intelligent Vehicles Symposium
Computer vision,Gaze,Situation awareness,Visualization,Computer science,Precision and recall,Vehicle dynamics,Artificial intelligence,Systems architecture,Accuracy and precision,Cognitive neuroscience of visual object recognition
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Sujitha Martin117712.72
Ashish Tawari221916.07