Head Tracking Using Particle Filter with Intensity Gradient and Color Histogram

This paper presents a method for tracking human head using a particle filter to naturally integrate two complementary cues: intensity gradient and color histogram. The shape of the head is modeled as an ellipse, along which an intensity gradient is estimated, while the interior appearance is modeled using a color histogram. These two cues play complementary roles in tracking a human head with free rotation on a cluttered background. To evaluate the tracker performance, we test with both synthetic image sequences and real sequences. Experiments show that the tracker is robust to 360-degree rotation of the head on a cluttered background