@inproceedings{bb7a4982c26c4e7e8e51e15513788def,
title = "Visual attention computation in video of driving environment",
abstract = "We here study the problem of visual attention computation in video of driving environment via the learning from eye movements. We collect a large-scale database of eye movements from 28 subjects on 30 videos of road scenes, which simulate the driving environment. The analysis on this eye movement database reveals that visual attention in driving environment is directed by high-level cognitive factors such as objects. We then present a new high-level representation called Traffic Object Bank (TOB), which is comprised of many individual road object detectors trained comprehensively in semantic space as well as viewpoint space. TOB provides semantically rich object-level features. Finally, we develop a computational model to predict where drivers look via the mapping from TOB-based representation and to gaze data. Experimental results on our traffic scene video benchmark indicate high accordance with human eye movement and show great promise for further applications.",
keywords = "Eye Movement, Salient Traffic Object Detection, Traffic Object Bank, Visual Attention",
author = "Junwei Han and Liye Sun and Dingwen Zhang and Xintao Hu and Gong Cheng and Lei Guo",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Multimedia and Expo, ICME 2014 ; Conference date: 14-07-2014 Through 18-07-2014",
year = "2014",
month = sep,
day = "3",
doi = "10.1109/ICME.2014.6890215",
language = "英语",
series = "Proceedings - IEEE International Conference on Multimedia and Expo",
publisher = "IEEE Computer Society",
number = "Septmber",
booktitle = "2014 IEEE International Conference on Multimedia and Expo, ICME 2014",
edition = "Septmber",
}