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Human tracking with multiple cameras based on face detection and mean shift
By: Asama, H.; Kaneko, T.; Ito, Y.; Yamashita, A.;
2011 / IEEE / 978-1-4577-2138-0
This item was taken from the IEEE Conference ' Human tracking with multiple cameras based on face detection and mean shift ' Human tracking is an important function to an automatic surveillance system using a vision sensor. Human face is one of the most significant features to detect person(s) in an image. However, face is not always observed from a single camera. Therefore, it is difficult to identify a person exactly in an image due to the variety of poses. This paper describes a method for automatic human tracking based on the face detection using Haar-like features and the mean shift tracking method. Additionally, the method increases its trackability by using multi-viewpoint images. The validity of the proposed method is shown through experiment.
Automatic Surveillance System
Most Significant Features
Automatic Human Tracking Method
Mean Shift Tracking Method
Image Color Analysis