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Bastos, R. & Dias, J. (2007). Skin Color Profile Capture for Scale and Rotation Invariant Hand Gesture Recognition. In Ana Rita Leitão, Miguel Sales Dias, Ricardo Jota (Ed.), Proc The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation 2007. Lisboa: ADETTI.

R. Bastos and J. M. Dias,  "Skin Color Profile Capture for Scale and Rotation Invariant Hand Gesture Recognition", in Proc The 7th Int. Workshop on Gesture in Human-Computer Interaction and Simulation 2007, Ana Rita Leitão, Miguel Sales Dias, Ricardo Jota, Ed., Lisboa, ADETTI, 2007

@inproceedings{bastos2007_1716167674312,
	author = "Bastos, R. and Dias, J.",
	title = "Skin Color Profile Capture for Scale and Rotation Invariant Hand Gesture Recognition",
	booktitle = "Proc The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation 2007",
	year = "2007",
	editor = "Ana Rita Leitão, Miguel Sales Dias, Ricardo Jota",
	volume = "",
	number = "",
	series = "",
	publisher = "ADETTI",
	address = "Lisboa",
	organization = "ADETTI - Associação para o Desenvolvimento das Telecomunicações e Técnicas de Informática",
	url = "https://www.jvrb.org/old-content/jvrb/pastconferences/PastConferences2007/gw2007/view"
}

TY  - CPAPER
TI  - Skin Color Profile Capture for Scale and Rotation Invariant Hand Gesture Recognition
T2  - Proc The 7th International Workshop on Gesture in Human-Computer Interaction and Simulation 2007
AU  - Bastos, R.
AU  - Dias, J.
PY  - 2007
CY  - Lisboa
UR  - https://www.jvrb.org/old-content/jvrb/pastconferences/PastConferences2007/gw2007/view
AB  - In this paper we present a new approach to real-time and rotation invariant hand pose
detection, which is based on a novel technique for computing the best hand skin profile.
This skin profile is used to classify each pixel in the current video frame as belonging
to the skin color or to the background and corresponds to a group of 3D line
segments (vectors), where the control points are important HSV (Hue-Saturation-
Value) 3D coordinates extracted during the skin capture stage. The runtime pixel
classification is evaluated by measuring the distance of each pixel HSV 3D cylindrical
coordinates to each one of formed vectors of the current skin profile. A space
transformation, from HSV cone to HSV 3D cylindrical coordinates, is performed due
to the Hue component discontinuity around the 360º, found in the HSV model, which
would prevent any direct arithmetic comparison between Hue values. After
skin/background segmentation, we construct efficient and reliable scale and rotation
invariant hand pose gesture descriptors, by introducing an innovative technique, referred
to as “oriented gesture descriptors”. These descriptors correspond to grayscale
image representations of the hand gesture captured during gesture acquisition. Finally,
hand pose recognition is computed using a template matching technique, which is
light invariant [BD05], between the acquired gestures/descriptors and the current
tracking gesture. The system takes into account the fact that a moving hand, in a dynamic
light environment, can present several variations of the predominant skin-tone,
instead of just using a single color tone as a reference, such as in [MOC06].
ER  -