PPT-Fitting : Voting and the Hough Transform

April 24 th 2018 Yong Jae Lee UC Davis Announcements PS0 grades are up on Canvas PS0 stats Mean 9338 Standard Dev 786 2 Last time Grouping Bottomup segmentation via clustering. CSE . 576. Ali Farhadi. Many slides from Steve Seitz and Larry . Zitnick. Edge. Attneave's. Cat (1954) . Edges are caused by a variety of factors. depth discontinuity. surface color discontinuity. illumination discontinuity. Lectures 7 & 8 . – Prof. . Fergus. Slides from: S. Lazebnik, S. Seitz, M. Pollefeys, A. Effros. . How do we build panorama?. We need to match (align) images. Matching with Features. Detect feature points in both images. LAQUESHA JONES. ELA 5. TH. /6. TH. MAY 8, 2015. HOUGH. The Neighborhood. HOUGH RIOTS. *Where & When*. The Hough Riots were race riots that took place in the predominately African-American area of Hough (huff) in Cleveland.. Computer Vision Lecture 11: The Hough Transform. 1. Fitting Curve Models to Edges. Most contours can be well described by combining several . : . Voting and the Hough Transform. Monday, Feb . 14. Prof. Kristen . Grauman. UT-Austin. Last time: Grouping. Bottom-up segmentation via clustering. To . find mid-level regions, tokens. General choices -- features, affinity functions, and clustering algorithms. : . Voting and the Hough Transform. Tues Feb 14. Kristen Grauman. UT Austin. Today. Grouping : wrap up clustering . algorithms. See slides from last time. Fitting : introduction to voting. Slide credit: Kristen Grauman. Matching. Region Representation. Image Alignment, Optical Flow. Lectures . 5 . & . 6. . – Prof. . Fergus. Slides from: S. Lazebnik, S. Seitz, M. Pollefeys, A. Effros. . Panoramas. Facebook 360 photos. Voting schemes. Let each feature vote for all the models that are compatible with it. Hopefully the noise features will not vote consistently for any single model. Missing data doesn’t matter as long as there are enough features remaining to agree on a good model. With thanks to: Harry . Chien. , Lisa Chan, . Bassem. El-Dasher, Gregory Rohrer. 1. Last revised:. 12. th. Apr. ‘14. 27-750. Texture, Microstructure & Anisotropy. A.D. Rollett. Overview. Understanding the diffraction patterns. Computational Aspect of Robotics. Many slides . from James Hays, Kristen Grauman, . Derek Hoiem, Lana Lazebnik, Steve Seitz, David Forsyth, David Lowe, Fei-Fei Li. Example: Line fitting. Why fit lines? . Image Alignment, Optical Flow. Lectures . 5 . & . 6. . – Prof. . Fergus. Slides from: S. Lazebnik, S. Seitz, M. Pollefeys, A. Effros. . Panoramas. Facebook 360 photos. How do we build panorama?. We would like to form a higher-level, more compact representation of the features in the image by grouping multiple features according to a simple model. Source: K. Grauman. Fitting. Choose a . parametric model . Photo by Carl Warner. Feature Matching and Robust Fitting. Computer Vision. James Hays. Acknowledgment: Many . slides from Derek . Hoiem. and . Grauman&Leibe. . 2008 AAAI Tutorial. Read . Szeliski. Fitting Models: . Hough Transform . & RANSAC. Prof. Adriana . Kovashka. University of Pittsburgh. October 19, . 2016. Plan for today. Last lecture: Detecting . edges . This lecture: Detecting . lines .