1. Computer Vision REU Week 2 Adam Kavanaugh

2. Video Canny Put canny into a loop in order to process multiple frames of a video sequence Put canny into a loop in order to process multiple frames of a video sequence Output each individual picture to its own directory for ease of processing Output each individual picture to its own directory for ease of processing

3. 10 Research Topics Search the Vision group sites of: Search the Vision group sites of: Cornell University Cornell University Carnegie Mellon University Carnegie Mellon University Stanford University Stanford University University of Cambridge University of Cambridge

4. Cornell University Detection and long term tracking of moving objects in aerial video Detection and long term tracking of moving objects in aerial video

5. Cornell University Model based tracking in quasi real-time Model based tracking in quasi real-time

6. Cornell University Recognizing Flexible Objects Recognizing Flexible Objects

7. Carnegie Mellon University AAM Fitting Algorithms AAM Fitting Algorithms Active Appearance Models (AAM) Active Appearance Models (AAM)

8. Carnegie Mellon University Gaze Estimation Gaze Estimation Uses an AAM algorithm to detect features like eye corners Uses an AAM algorithm to detect features like eye corners

9. Carnegie Mellon University 2D->3D Face Model Construction 2D->3D Face Model Construction Uniquely recovers the 3D non-rigid shapes and poses of a human face from a 2D monocular video Uniquely recovers the 3D non-rigid shapes and poses of a human face from a 2D monocular video

10. Carnegie Mellon University Scene Flow Scene Flow Scene flow is the three-dimensional motion field of points in the world Scene flow is the three-dimensional motion field of points in the world Optical flow in 3D! Optical flow in 3D!

11. Stanford University Edge, Corner, and Junction Detection with the Generalized Compass Operator Edge, Corner, and Junction Detection with the Generalized Compass Operator Find edges were Canny fails Find edges were Canny fails

12. Stanford University Elliptical Head Tracking Using Intensity Gradients and Color Histograms Elliptical Head Tracking Using Intensity Gradients and Color Histograms In real time, the tracker is able to reliably and automatically control the camera's pan, tilt, and zoom in order to keep the subject centered in the field of view at a desired size. In real time, the tracker is able to reliably and automatically control the camera's pan, tilt, and zoom in order to keep the subject centered in the field of view at a desired size.

13. University of Cambridge Image Divergence from Closed Curves Image Divergence from Closed Curves Finds time to contact and surface orientation reliably Finds time to contact and surface orientation reliably This is exploited in real-time visual docking and obstacle avoidance. This is exploited in real-time visual docking and obstacle avoidance.

14. Lucas Kanade C conversion In Progress… In Progress… On line 71 of the MATLAB file On line 71 of the MATLAB file Compiles but no runtime tests have been made Compiles but no runtime tests have been made C file is already twice as large as the MATLAB file C file is already twice as large as the MATLAB file I understand why Alex recommended doing this coding in MATLAB! I understand why Alex recommended doing this coding in MATLAB!