Efros Martial Hebert Carnegie Mellon University dhoiemefroshebert cscmuedu Abstract Many computer vision algorithms limit their performance by ignoring the underlying 3D geometric structure in the image We show that we can estimate the coarse geomet
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Geometric Context from a Single Image Derek Hoiem Alexei A
Presentation on theme: "Geometric Context from a Single Image Derek Hoiem Alexei A"— Presentation transcript:
Geometric Context from a Single Image Derek Hoiem Alexei A - Description
Efros Martial Hebert Carnegie Mellon University dhoiemefroshebert cscmuedu Abstract Many computer vision algorithms limit their performance by ignoring the underlying 3D geometric structure in the image We show that we can estimate the coarse geomet ID: 8921 Download Pdf
Efros Martial Hebert Carnegie Mellon University Robotics Institute dhoiemefroshebert cscmuedu Abstract Image understanding requires not only individually esti mating elements of the visual world but also capturing the interplay among them In this pa
Efros Carnegie Mellon University Carsten Rother John Winn Antonio Criminisi Microsoft Research Cambridge Figure 1 Starting with a present day photograph of the famous Abbey Road in London left a person using our system was easily able to make the sc
edu Abstract We propose to shift the goal of recognition from naming to describing Doing so allows us not only to name famil iar objects but also to report unusual aspects of a famil iar object spotty dog not just dog to say something about unfamilia
We present an approach to interpret the major surfaces ob jects and support relations of an indoor scene from an RGBD image Most existing work ignores physical interactions or is applied only to tidy rooms and hallways Our goal is to parse typical o
Methods for Geometric Correction. Parametric (analytical). Mathematically models effects of sensor geometry and motion to derive accurate correction equations for correcting the coordinates of each pixel.
Michael . Drabkin. MD. Lauren Senior, Uma Kanth, Allison Rubin MD, Steven Lev MD. ASNR 2015 Annual . Meeting. eEdE. #: eEdE-85. Control #: 772 . Disclosures. Nothing to disclose.. Purpose. To provide the radiologist with a pattern approach to head CT interpretation based on templates of interconnected geometric shapes. The viewer is encouraged to think from general to specific and consider spatial relationships. Cases will demonstrate the utility of this framework to everyday practice..
What is High-Dynamic-Range Image?. http://en.wikipedia.org/wiki/High-dynamic-range_imaging. Single-Jeopardy. What is the use of Bayer Pattern?. To reduce the manufacture cost (from 3-CCD to single-CCD).
Light travels in a STRAIGHT LINE . ANOTHER WAY TO THINK OF LIGHT. Light leaving the candle travels in all directions, but we only SEE the light that travels in to our Eye-Brain. ANOTHER WAY TO THINK OF .
Efros and Martial Hebert Robotics Institute Carnegie Mellon University Abstract Since most current scene understanding approaches operate either on the 2D image or using a surfacebased representation they do not allow reasoning about the physical co