Hand-tracking in Video Conversations
Name
Pihel Saatmann
Abstract
This thesis describes some of the more common techniques for object tracking and an implementation of the colour-based tracking algorithm known as CAMShift. The algorithm is implemented as part of a simple object tracking plug-in for the video annotation tool ANVIL. The tracker can be used to automatically annotate hand gestures or the movements of any object that is distinguishable from its background. The plug-in records velocity, duration and total travel distance of hand gestures and outputs the recorded data to an annotation file. The tracker was tested on real recordings of dialogues and the results were compared to manually created annotations for hand gestures. Testing and evaluation revealed that data recorded by the tracker is not accurate enough to provide a complete alternative to manual annotation, but could rather be used as a basis for determining where hand gestures can be detected. Thus using the tracker in combination with a human annotator could significantly speed up the annotation process.
Graduation Thesis language
English
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Päivi Kristiina Jokinen
Defence year
2014