Name
Abstract | ||
|---|---|---|
This paper proposes a method to explore the user's navigation foci and visual tracks by estimating gaze points and mapping them to the objects of video content. The tracking method for multiple objects is derived from the adaptive weight based feature with probability densities. It is able to track the target objects efficiently even when the target objects are lost. It continuously applies sequence scheme and mean scheme throughout to track objects while they are lost. The experimental results demonstrate the proposed method provide higher robustness under different conditions. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICMLC.2014.7009155 | ICMLC |
Keywords | Field | DocType |
object tracking,video signal processing,user navigation foci exploration method,adaptive weight,gaze tracking,probability densities,video content,feature extraction,image sequences,sequence scheme,mean scheme,progress threshold,lost object tracking,integrated object tracking technique,adaptive weight based feature,integrated gaze tracking technique,probability,gaze point estimation,navigation,image segmentation | Computer vision,Pattern recognition,Gaze,Computer science,Tracking system,Image segmentation,Robustness (computer science),Video tracking,Artificial intelligence | Conference |
Volume | ISSN | ISBN |
1 | 2160-133X | 978-1-4799-4216-9 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chiao-Wen Kao | 1 | 3 | 1.41 |
| Bor-Jiunn Hwang | 2 | 45 | 12.62 |
| Chaur-Heh Hsieh | 3 | 0 | 0.34 |
| Yun-Ting Huang | 4 | 0 | 0.34 |
| Hui-Hui Chen | 5 | 0 | 0.34 |
| Shyi-Huey Wu | 6 | 0 | 0.68 |