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Incorporating skin color for improved face Detection and tracking system – 2016

Project Title:

Incorporating skin color for improved face Detection and tracking system – 2016

Abstract:

Face detection and tracking have wide applications, for example, law enforcement, gaming, image search, marketing, etc. The detection and tracking tasks are quite challenging. Tracking the face in an image includes gender identification and segmenting the face using the skin color. In the past, many methods have been proposed to identify a face in videos, such as feature-based detection, skin color segmentation, appearance, and eigen-based identification. These techniques use image classifiers (both weak and strong) but are not very accurate. This paper introduces a hybrid method that utilizes skin color for increasing accuracy of detection and tracking. In our method, an image is rescaled and divided based on skin color, using RGB (red-green-blue) color combinations. The divided skin tone image is combined with the edges of images before applying the morphological operations. As a final step, a bounding box appears on the detected face.

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