Abstract: Energy consumption is an important design issue for
Mobile Subscriber Station (MSS) in the standard IEEE 802.16e.
Because mobility of MSS implies that energy saving becomes an
issue so that lifetime of MSS can be extended before re-charging.
Also, the mechanism in efficiently managing the limited energy is
becoming very significant since a MSS is generally energized by
battery. For these, sleep mode operation is recently specified in the
MAC (Medium Access Control) protocol. In order to reduce the
energy consumption, we focus on the sleep-mode and wake-mode of
the MAC layer, which are included in the IEEE 802.16 standards [1-
2].
Abstract: Skin color based tracking techniques often assume a
static skin color model obtained either from an offline set of library
images or the first few frames of a video stream. These models
can show a weak performance in presence of changing lighting or
imaging conditions. We propose an adaptive skin color model based
on the Gaussian mixture model to handle the changing conditions.
Initial estimation of the number and weights of skin color clusters
are obtained using a modified form of the general Expectation
maximization algorithm, The model adapts to changes in imaging
conditions and refines the model parameters dynamically using spatial
and temporal constraints. Experimental results show that the method
can be used in effectively tracking of hand and face regions.