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Human face detector: an enhancement of eigenfaces and gaussian pyramid-based human face detection algorithm / Mary Ann Gualas and Janairo Jiao. 6

By: Mary Ann Gualas an Janairo Jiao. 4 0 16, [, ] | [, ] |

Contributor(s): 5 6 [] |

Language: Unknown language code Summary language: Unknown language code Original language: Unknown language code Series: ; 200346Edition: Description: 28 cmContent type: text Media type: unmediated Carrier type: volumeISBN: ISSN: 2Other title: 6 []Uniform titles: | | Related works: 1 40 6 []Subject(s): -- 2 -- 0 -- -- | -- 2 -- 0 -- 6 -- | 2 0 -- | -- -- 20 -- | | -- -- -- -- 20 -- | -- -- -- 20 -- --Genre/Form: -- 2 -- Additional physical formats: DDC classification: | LOC classification: | | 2Other classification:

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Action note: In: Summary: ABSTRACT: This thesis entitled Human Face Detector (An Enhancement of Eigenfaces and Gaussian Pyramids-based Human Face Detection Algorithm) was a study based on the algorithm presented by Babback Moghaddam and Alex Pentland. Its with a way of detecting human faces on a given image. This could be done by inputting an image with human faces on it and then it outputs the image with face in it outlined by a rubber band box. There are cases wherein the Human Face Detector cannot detect faces of human and sometimes, even recognizes or detects any type of object. It also fails to detect all faces present in an input image. In addition, there are times when faces in an image that appeared in side views were certain to be missed. Here, an enhanced algorithm was formulated. New features were added in order to enhance the detecting capabilities of the existing algorithm. The enhanced algorithm uses facial features in order to to ensure that only human faces will be detected at all times. The use of distance in face space and distance from face space as well as the use of multiple detection was also added in order to contribute in accurate detection of human faces. With the added features, the said algorithm was able to perform a much better detection results. Thus, the enhancement of the said algorithm made it a more reliable Human Face Detector. Other editions:

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Item type	Current location	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	PLM	PLM Archives	Filipiniana-Thesis	QA76.76 .G84 2003 (Browse shelf)	Available		FT3666

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Undergraduate Thesis: (Bachelor of Science in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2003. 56

ABSTRACT: This thesis entitled Human Face Detector (An Enhancement of Eigenfaces and Gaussian Pyramids-based Human Face Detection Algorithm) was a study based on the algorithm presented by Babback Moghaddam and Alex Pentland. Its with a way of detecting human faces on a given image. This could be done by inputting an image with human faces on it and then it outputs the image with face in it outlined by a rubber band box. There are cases wherein the Human Face Detector cannot detect faces of human and sometimes, even recognizes or detects any type of object. It also fails to detect all faces present in an input image. In addition, there are times when faces in an image that appeared in side views were certain to be missed. Here, an enhanced algorithm was formulated. New features were added in order to enhance the detecting capabilities of the existing algorithm. The enhanced algorithm uses facial features in order to to ensure that only human faces will be detected at all times. The use of distance in face space and distance from face space as well as the use of multiple detection was also added in order to contribute in accurate detection of human faces. With the added features, the said algorithm was able to perform a much better detection results. Thus, the enhancement of the said algorithm made it a more reliable Human Face Detector.

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