Tracking Occluded Objects Using Kalman Filter and Color Information

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.