@article{1851,
  author = {Noha Sarhan, Yasser El-Sonbaty, Sherin Youssef},
  title = {Towards a Fast Moving Object Detection Method},
  journal = {Journal of Data Processing},
  year = {2015},
  volume = {5},
  number = {2},
  doi = {},
  url = {http://www.dline.info/jdp/fulltext/v5n2/v5n2_3.pdf},
  abstract = {Depth information plays an important role in many computer vision applications including moving object
detection. In this paper, we introduce a fast moving object detection method using Kinect v2. Comparing to Kinect v1, the
Kinect v2 provides a higher resolution for RGB images and adopts a ToF (Time-of-Flight) sensing mechanism for depth
measurement. The upgraded depth sensing method yields depth images with less noises and holes, which allows us to simplify
the pre-processing of eliminating noises and filling holes. Also, the depth information of the Kinect v2 is fruitful enough to
detect the moving object without resorting to RGB image. These properties of the Kinect v2 lead us to devise a fast moving
object detection method.},
}