Component-based online learning for face detection and verification
KM Lee - … Conference on Computational and Information Science, 2005 - Springer
KM Lee
International Conference on Computational and Information Science, 2005•SpringerComponent detectors can accurately locate facial components, and component-based
approaches can be used to build detectors that can handle partial occlusions. This paper
proposes a face detection and verification method using component-based online learning.
The main difference from previously reported component-based approaches is the use of
online learning, which is ideal for highly repetitive tasks. This results in faster and more
accurate face detection, because system performance improves with continued use. Further …
approaches can be used to build detectors that can handle partial occlusions. This paper
proposes a face detection and verification method using component-based online learning.
The main difference from previously reported component-based approaches is the use of
online learning, which is ideal for highly repetitive tasks. This results in faster and more
accurate face detection, because system performance improves with continued use. Further …
Abstract
Component detectors can accurately locate facial components, and component-based approaches can be used to build detectors that can handle partial occlusions. This paper proposes a face detection and verification method using component-based online learning. The main difference from previously reported component-based approaches is the use of online learning, which is ideal for highly repetitive tasks. This results in faster and more accurate face detection, because system performance improves with continued use. Further, uncertainty is added by calculating the standard deviation of face components and their relations.
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