  This study proposes an approach to segment human object from a depth image
based on histogram of depth values. The region of interest is first extracted
based on a predefined threshold for histogram regions. A region growing process
is then employed to separate multiple human bodies with the same depth
interval. Our contribution is the identification of an adaptive growth
threshold based on the detected histogram region. To demonstrate the
effectiveness of the proposed method, an application in driver distraction
detection was introduced. After successfully extracting the driver's position
inside the car, we came up with a simple solution to track the driver motion.
With the analysis of the difference between initial and current frame, a change
of cluster position or depth value in the interested region, which cross the
preset threshold, is considered as a distracted activity. The experiment
results demonstrated the success of the algorithm in detecting typical
distracted driving activities such as using phone for calling or texting,
adjusting internal devices and drinking in real time.
