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We talked about Filters Edges Corners Interest Points Descriptors Image Stitching Stereo SFM
We talked about Reconstruction Flow Face Detection Face Recognition Pedestrian Detection Part-Based Recognition …
What else? Several other interesting stuff that we wanted to talk about them
Person Sky Tree Car Image Segmentation
drive- way sky house ? grass Context-aware visual discovery grass sky truck house ? drive- way grass sky house drive- way fence ? ? ?? 10 Context in supervised recognition: [Torralba 2003], [Hoiem et al. 2006], [He et al. 2004], [Shotton et al. 2006], [Heitz & Koller 2008], [Rabinovich et al. 2007], [Galleguillos et al. 2008], [Tu 2008], [Parikh et al. 2008], [Gould et al. 2009], [Malisiewicz & Efros 2009], [Lazebnik 2009]
Attributes Vehicle Wheel Animal Leg Head Four-legged Mammal Can run Can Jump Is Herbivorous Facing right Moves on road Facing right
Describing Images Using Attributes. Describing Images Farhadi et.al. CVPR 2009.
Are Categories Necessary in a Data-Rich World? Alexei (Alyosha) Efros CMU Joint work with Tomasz Malisiewicz.
Object recognition (part 2) CSE P 576 Larry Zitnick
1 Recognition by Association: ask not “What is it?” ask “What is it like?” Tomasz Malisiewicz and Alyosha Efros CMU CVPR’08.
Putting Objects in Perspective Derek Hoiem Alexei A. Efros Martial Hebert Carnegie Mellon University Robotics Institute.
Course Overview What is AI? What are the Major Challenges? What are the Main Techniques? Where are we failing, and why? Step back and look at.
Kapitel 14 Recognition – p. 1 Recognition Scene understanding / visual object categorization Pose clustering Object recognition by local features Image.
CVPR2013 Poster Modeling Actions through State Changes.
Right or Wrong? To consider what course of action is right and why.
Elements of Film Basic Film Terms. Shot: a segment of film; an image that begins when the camera is started and ends either when the camera is stopped.
YEAR 7 Things to think about for year 7 drama lessons.
Feature matching “What stuff in the left image matches with stuff on the right?” Necessary for automatic panorama stitching (Part of Project 4!) Slides.
Emergency Medical Response Scenario 1: You Are the Emergency Medical Responder You are called to the scene of an industrial plant after a report of an.
Calais Darrell December 15 th Introduction Road safety is very important, and that is what this power point is going to tell you about. It will.
Your project name goes here. Add a picture Add a caption to go with the picture saying something important about the project.
The Problem with the Blank Slate Approach Derek Hoiem Beckman Institute, UIUC * unpublished *
Attributes for Classifier Feedback Amar Parkash and Devi Parikh.
Unit 2 Theres no shouting and no running. Barbara Shen.
Evidential modeling for pose estimation Fabio Cuzzolin, Ruggero Frezza Computer Science Department UCLA.
Operational Research (O.R.) case studies. What’s the problem?
Studying films The technical stuff. What makes a film? There are lots of important techniques used to make films interesting to watch. We are going to.
Question 1 Dana is driving her car 150mph to the northwest. 150mph to the northwest is Danas A.Acceleration B.Velocity C.Average Speed D.Motion.
3.1.spi.9: Determine word meanings through the use of context clues. Using the explanation clues, what do the underlined words mean? Precipitation, such.
Exploiting Big Data via Attributes (Offline Contd.)
Summarize things so far… Distance (m) Time (sec) What is the object’s speed from: 0-3 sec: 3-5 sec: 5-11 sec:
Quiz Time What button stops the sprite from vanishing off the screen?
H University Bicycle Contest Study Guide. Identification: Brakes.
Feature extraction: Corners 9300 Harris Corners Pkwy, Charlotte, NC.
A. as is a couldn’t does could has wouldn’t.
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