PPT-HOUGH RIOTS

LAQUESHA JONES ELA 5 TH 6 TH MAY 8 2015 HOUGH The Neighborhood HOUGH RIOTS Where amp When The Hough Riots were race riots that took place in the predominately AfricanAmerican area of Hough huff in Cleveland. . Your. . Attitude. Staying Positive. Even in a Negative Environment. WYTRANS Conference . July 16, 2011. Do you recognize any of these characters?. Know-it-All. Griper. Drama Queen. Steamer. Perfectionist. 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. Mrs. . Gregovich. History through Film. To Accompany “Uprising: Hip Hop and The L.A. Riots”. Vocabulary. Residential Segregation. Civil Rights Legislation. Riot. The physical separation of two groups based on residence and housing; sorts populations into various neighborhood contexts and shapes the living environment at the neighborhood level.. An analysis of 2 incidents in Singapore’s history . Jiang Zhifeng. Faustina Joyce Fernando. Shawn Ho Cheng Ying. 1. VS.. 2. Hock Lee Bus Riots. 3. Little India Riots. 4. Assess if the 2 incidents can be considered as “riots”. Flashcards. building tenders . building tenders . inmates who were tacitly acknowledged by prison administrators to have informal social control of a given inmate area . close-custody unit. close-custody unit. Origin of riots. Riots were sparked off by increase in fare increase in Brazil’s public transportation in major cities like Sao Paulo, Rio de Janeiro. This was initially led by students who wanted bus fares to be free. . : . 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. 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? . April 24. th. , 2018. Yong Jae Lee. UC Davis. Announcements. PS0 grades are up on . Canvas. PS0 stats:. Mean: . 93.38. Standard Dev. : . 7.86. 2. Last time: Grouping. Bottom-up segmentation via clustering. 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?. 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 .