Abstract—Robust visual tracking is imperative to track
multiple occluded objects. Kalman filter and color information
tracking algorithms are implemented independently in most of
the current research. The proposed method combines extended
Kalman filter with past and color information for tracking
multiple objects under high occlusion. The proposed method is
robust to background modeling technique. Object detection is
done using spatio-temporal Gaussian mixture model
(STGMM). Tracking consists of two steps: partially occluded
object tracking and highly occluded object tracking. Tracking
partially occluded objects, extended Kalman filter is exploited
with past information of object, whereas for highly occluded
object tracking, color information and size attributes are used.
The system was tested in real world application and successful
results were obtained.
Index Terms—EKF with color, tracking occluded objects,
STGMM, robust tracking using color information.
Malik M. Khan, T. W. Awan, I. Kim and Y. Soh are with Myongji
University, Yongin, Korea (e-mail: kit@mju.ac.kr).
[PDF]
Cite:Malik M. Khan, Tayyab W. Awan, Intaek Kim, and Youngsung Soh, "Tracking Occluded Objects Using Kalman Filter and Color Information," International Journal of Computer Theory and Engineering vol. 6, no. 5, pp. 438-442, 2014.
