Gesture recognizing using segmentation of dynamic hand image based on the mixture of Gaussians model and skin color / Reconhecimento de gestos usando segmentação de imagens dinâmicas de mãos baseada no modelo de mistura de gaussianas e cor de pele

AUTOR(ES)
DATA DE PUBLICAÇÃO

2006

RESUMO

The purpose of this paper is to develop a methodology able to recognize hand gestures from dynamic images to interact with systems. After the image capture segmentation takes place where pixels belonging to the hands are separated from the background based on skin-color segmentation and background extraction. The image preprocessing can be applied before the edge detection. The recognition algorithm uses edges only; therefore it is quick enough for real time. The largest blob from the segmented image will be considered as the hand region. The detected regions are analyzed to determine position and orientation of the hand for each frame. The position and other attributes of the hands are tracked per frame to distinguish a movement from the hand in relation to the background and from other objects in movement, and to extract the information of the movement for the recognition of dynamic gestures. Based in the collected position, movement and indications of position are calculated to recognize a significant gesture.

ASSUNTO(S)

hand gesture human computer interaction (hci) gesture recognition computer vision invariants moments reconhecimento de gestos mistura de gaussianas mixture of gaussians visão computacional segmentação skin color cor de pele momentos invariantes interação humano-computador (ihc) segmentation gestos de mão

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