Difference between revisions of "Robot Perception"
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=Object Recognition= | =Object Recognition= | ||
| − | + | * [http://www.robot-intelligence.kr/index.php/Object_Recognition Object Recognition] | |
| − | * | + | <br /> |
| − | + | ||
=Human Tracking and Behavior Analysis= | =Human Tracking and Behavior Analysis= | ||
| − | * | + | ==Concept== |
| + | * For human tracking, we are studying a method of tracking-by-detection, which use the combined visual features such as color, LBP and intensity. | ||
| + | * For human activity analysis, SGT(Situation Graph Tree) is introduced for easily utilizing the domain knowledge about abnormal behaviors. | ||
| + | * Our overall s/w schema is as follows: | ||
| + | ::[[File:behavior-analysis.jpg|800px|left]] | ||
| + | <br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/> | ||
| + | |||
| + | ==Related Papers== | ||
| + | *Chansu Kim and Sung-Kee Park,"Modified Particle Filtering using Foreground Separation and Confidence for Object Tracking," IEEE Advanced Video and Signal-based Surveillance, 2016. | ||
Latest revision as of 19:26, 17 June 2016
Object Recognition
Human Tracking and Behavior Analysis
Concept
- For human tracking, we are studying a method of tracking-by-detection, which use the combined visual features such as color, LBP and intensity.
- For human activity analysis, SGT(Situation Graph Tree) is introduced for easily utilizing the domain knowledge about abnormal behaviors.
- Our overall s/w schema is as follows:
Related Papers
- Chansu Kim and Sung-Kee Park,"Modified Particle Filtering using Foreground Separation and Confidence for Object Tracking," IEEE Advanced Video and Signal-based Surveillance, 2016.
