'Flow vectors' presentation slideshows

Optic Flow and Motion Detection

Optic Flow and Motion Detection. Computer Vision and Imaging Martin Jagersand. Readings: Szeliski Ch 8 3DV Ma, Kosecka, Sastry Ch 4. Image motion. Somehow quantify the frame-to-frame differences in image sequences. Image intensity difference. Optic flow 3-6 dim image motion computation.

850 views • 84 slides

Optic Flow and Motion Detection

Optic Flow and Motion Detection. Cmput 615 Martin Jagersand. Image motion. Somehow quantify the frame-to-frame differences in image sequences. Image intensity difference. Optic flow 3-6 dim image motion computation. Motion is used to:.

752 views • 74 slides

Motion in 2D image sequences

Motion in 2D image sequences. Definitely used in human vision Object detection and tracking Navigation and obstacle avoidance Analysis of actions or activities Segmentation and understanding of video sequences. Frame from an ARDA Sample Video. Change detection for surveillance.

442 views • 44 slides

Motion in 2D image sequences

436 views • 42 slides

k-Indistinguishable Traffic Padding in Web-Based Applications

k-Indistinguishable Traffic Padding in Web-Based Applications. Presenter: Wen Ming Liu (Concordia University) Joint work with: Lingyu Wang (Concordia University ) Kui Ren (Illinois Institute of Technology) Pengsu Cheng (Concordia University ) Mourad Debbabi (Concordia University)

591 views • 41 slides

k-Indistinguishable Traffic Padding in Web-Based Applications

k-Indistinguishable Traffic Padding in Web-Based Applications. Presenter: Wen Ming Liu (Concordia University) Joint work with: Lingyu Wang (Concordia University ) Kui Ren (Illinois Institute of Technology) Pengsu Cheng (Concordia University ) Mourad Debbabi (Concordia University)

417 views • 41 slides

Motion in 2D image sequences

Motion in 2D image sequences. Definitely used in human vision Object detection and tracking Navigation and obstacle avoidance Analysis of actions or activities Segmentation and understanding of video sequences. Frame from an ARDA Sample Video. Change detection for surveillance.

540 views • 36 slides

CAP 5415 Computer Vision Fall 2004

CAP 5415 Computer Vision Fall 2004. Dr. Alper Yilmaz Univ. of Central Florida www.cs.ucf.edu/courses/cap5415/fall2004 Office: CSB 250. Recap Epipolar Geometry. Essential matrix Fundamental matrix. P. x l. P l. x r. P r. C l. C r. epipole. epipole. Recap 8-Point Algorithm.

187 views • 7 slides