Presentation is loading. Please wait.

Presentation is loading. Please wait.

Introduction to Object Tracking Presented by Youyou Wang CS643 Texas A&M University.

Similar presentations


Presentation on theme: "Introduction to Object Tracking Presented by Youyou Wang CS643 Texas A&M University."— Presentation transcript:

1 Introduction to Object Tracking Presented by Youyou Wang CS643 Texas A&M University

2 Outlines Introduction Introduction Representation Representation Feature Selection Feature Selection Object Detection Object Detection Object Tracking Object Tracking Future Directions Future Directions

3 Introduction- Objectives Object tracking is an important task within the field of computer vision. motion-based recognition automated surveillance video indexing human-computer interaction traffic monitoring vehicle navigation

4 Introduction - Problems —loss of information caused by projection of the 3D world on a 2D image, —noise in images, —complex object motion, —nonrigid or articulated nature of objects, —partial and full object occlusions, —complex object shapes, —scene illumination changes, —real-time processing requirements.

5 Outlines Introduction Introduction Representation Representation Shape Shape Appearance Appearance Feature Selection Feature Selection Object Detection Object Detection Object Tracking Object Tracking Future Directions Future Directions

6 Representation- Shape —Points. —Object silhouette and contour. —Primitive geometric shapes. —Articulated shape models. —Skeletal models.

7 Representation- Appearance Probability densities of object appearance Templates Active appearance models Multi-view appearance models

8 Outlines Introduction Introduction Representation Representation Feature Selection Feature Selection Object Detection Object Detection Object Tracking Object Tracking Future Directions Future Directions

9 Feature Selection Color Color Edge Edge Texture Texture Optical Flow Optical Flow

10 Outlines Introduction Introduction Representation Representation Feature Selection Feature Selection Object Detection Object Detection Point detector Point detector Background subtraction Background subtraction Image segmentation Image segmentation Supervised learning Supervised learning Object Tracking Object Tracking Future Directions Future Directions

11 Object Detection- Point Detector Point Detector Point Detector Fine/LowCoarse/High SIFT (Lowe) 2 Find local maximum of: –Difference of Gaussians in space and scale scale x y  DoG  Harris Harris SIFT SIFT KLT KLT

12 Object Detection- Background Subtraction Background Subtraction Background Subtraction Mixture of Gaussian Mixture of Gaussian Eigen-background Eigen-background

13 Object Detection- Segmentation Image Segmentation Image Segmentation Mean-shift Mean-shift Graph-cut Graph-cut Active Contour Active Contour

14 Object Detection-Supervised Learning Supervised Learning Supervised Learning Ada-boosting Ada-boosting SVM SVM

15 Outlines Introduction Introduction Representation Representation Feature Selection Feature Selection Object Detection Object Detection Object Tracking Object Tracking Point Tracking Point Tracking Kernel Tracking Kernel Tracking Silhouette Tracking Silhouette Tracking Future Directions Future Directions

16 Object Tracking Point Tracking Point Tracking Kernel Tracking Kernel Tracking Silhouette Tracking Silhouette Tracking

17 Object Tracking – Point Tracking Deterministic Methods for Correspondence —Proximity —Maximum velocity —Small velocity change —Common motion —Rigidity

18 Object Tracking – Point Tracking Statistical Methods for Correspondence Kalman Filters Particle Filters x Posterior

19 Object Tracking – Point Tracking http://www.youtube.com/watch?v=6TG_p DEhXME&feature=related http://www.youtube.com/watch?v=6TG_p DEhXME&feature=related

20 Object Tracking – Kernel Tracking Template and Density-Based Appearance Models Multiview Appearance Models

21 Object Tracking – Kernel Tracking http://www.youtube.com/watch?v=tbHWv PWhVh8&feature=related http://www.youtube.com/watch?v=tbHWv PWhVh8&feature=related

22 Object Tracking - Silhouette Tracking Shape Matching Contour Tracking

23 Object Tracking - Silhouette Tracking http://www.youtube.com/watch?v=OpDjj NRfWZ4&feature=related http://www.youtube.com/watch?v=OpDjj NRfWZ4&feature=related http://www.youtube.com/watch?v=OpDjj NRfWZ4&feature=related http://www.youtube.com/watch?v=OpDjj NRfWZ4&feature=related http://www.youtube.com/watch?v=WIoGd hkfNVE&feature=related http://www.youtube.com/watch?v=WIoGd hkfNVE&feature=related

24 Outlines Introduction Introduction Representation Representation Feature Selection Feature Selection Object Detection Object Detection Object Tracking Object Tracking Future Directions Future Directions

25 Future Direction Directions Integration of contextual information. Online Learning Problems smoothness of motion minimal amount of occlusion illumination constancy high contrast with respect to background

26 Thank You


Download ppt "Introduction to Object Tracking Presented by Youyou Wang CS643 Texas A&M University."

Similar presentations


Ads by Google