Building a Robust Appearance Model for Object Tracking
2009pp. 471–475
Citations Over Time
Abstract
One of the challenges to creating robust trackers is the construction of robust appearance Model. This paper presents a robust appearance model for object tracking. The robust object distribution is acquired by comparing the two Gaussian Mixture Models of the object and background. The probability image generated by the robust object distribution is used for the CAMSHIFT tracking. Experiments on several video sequences show the effectiveness of the proposed method.
Related Papers
- → Object tracking via collaborative multi-task learning and appearance model updating(2015)12 cited
- → Co-trained generative and discriminative trackers with cascade particle filter(2013)7 cited
- → Cascaded Generative and Discriminative Learning for Visual Tracking(2013)2 cited
- → Real-Time Tracking via Deformable Structure Regression Learning(2014)1 cited