'Single pixel' presentation slideshows

Motion estimation

Motion estimation. Introduction to Computer Vision CS223B, Winter 2005 Richard Szeliski. Why Visual Motion?. Visual Motion can be annoying Camera instabilities, jitter Measure it. Remove it. Visual Motion indicates dynamics in the scene Moving objects, behavior

2.21k views • 116 slides

C280, Computer Vision

1.25k views • 112 slides

Informatics

Informatics. Module 7 Part 3. Fundamental Knowledge. Basic Computer Terminology Integrating Healthcare Enterprise (IHE) PACS Radiology Information System (RIS) Hospital Information System (HIS) Electronic Medical Record (EMR) Health Level 7 (HL7) Networks Film Digitizers

1.2k views • 94 slides

CPSC 641: Computer Graphics Image Formation

CPSC 641: Computer Graphics Image Formation. Jinxiang Chai. Are They Images?. Outline. Color representation Image representation Pin-hole Camera Projection matrix Plenoptic function. Outline. Color representation Image representation Pin-hole Camera Projection matrix

1.12k views • 91 slides

Region Growing - Splitting

Region Growing - Splitting. Segmentation can never be perfect there are extra or missing regions Correct the results of segmentation delete extra regions or merge regions with others split regions into more regions Correction criteria: significance (e.g., size)

1.38k views • 56 slides

Fire Detection using Geostationary and Polar Orbiting Satellites

Fire Detection using Geostationary and Polar Orbiting Satellites. Dr. Bernadette Connell CIRA/CSU/RAMMT Dr. Vilma Castro UCR/RMTC March 2005. Objectives. Background Environmental and weather conditions conducive to fires Satellite fire detection techniques for hot spots Examples

632 views • 45 slides

665 views • 44 slides

Image Printing and Display

Image Printing and Display. Reproducing reality. Display. Images are meant to be viewed Television screen Computer monitor Cell phone display Newspaper Glossy magazine Overhead projector Display device will be characterized by pixel shape spatial resolution color depth.

617 views • 44 slides

Curved Surfaces

1.39k views • 40 slides

Point Processing

Point Processing. Basic Image Processing Operations Arithmetic Operations Histograms. Basic Image Processing Operations. Image-Processing operations may be divided into 3 classes based on information required to perform the transformation. . Transforms

707 views • 38 slides

CNM 190 Advanced Digital Animation Lec 08 : Procedural Modeling Basics

CNM 190 Advanced Digital Animation Lec 08 : Procedural Modeling Basics. Jeff Ventrella, www.ventrella.com. Dan Garcia , EECS (co-instructor) Jeremy Huddleston, EECS (co-instructor). Dan on Procedural Modeling Basics Great references A note before starting What IS it? Why would you use it?

497 views • 37 slides

Computer Graphics

Computer Graphics. Lecture 9 Antialiasing, Texture Mapping. Today. Texture mapping Common texture coordinates mapping Texture coordinates Antialiasing Antialiasing-textures. 2. Texture Mapping : Why needed?. We don't want to represent all this detail with colour / geometry.

454 views • 36 slides

Section 4: Parallel Algorithms

459 views • 35 slides

Andrew Cosand ECE CVRR CSE 291 11-1-01

An Iterative Image Registration Technique with an Application to Stereo Vision Bruce D. Lucas & Takeo Kanade & Determining Optical Flow B. K. P. Horn & B. G. Schunck. Andrew Cosand ECE CVRR CSE 291 11-1-01. Image Registration. Basic Problem. Image Registration.

562 views • 33 slides

Digital Images

407 views • 26 slides

Image acquisition using sparse (pseudo)-random matrices

Image acquisition using sparse (pseudo)-random matrices. Piotr Indyk MIT. Outline. Sparse recovery using sparse random matrices Using sparse matrices for image acquisition. Ax. A. =. x.

414 views • 26 slides

Picking

Picking. What is picking?. Selecting an object on the screen What does this require? Get Mouse Location Compute what objects are rendered at the position. Example. How to do it. http://www.opengl.org/resources/faq/technical/selection.htm

404 views • 23 slides

CS361

Week 7 - Wednesday. CS361. Last time. What did we talk about last time? Transparency Gamma correction Texturing. Questions?. Project 2. Student Lecture: Mipmapping and Anisotropic filtering of Textures. Image Texturing. Image texturing. Usually, texturing is image texturing:

403 views • 22 slides

ASKAP Signal Processing Overview DIFX Users and Developers Meeting

331 views • 13 slides

Compressive Sensing for Multimedia Communications in Wireless Sensor Networks

Compressive Sensing for Multimedia Communications in Wireless Sensor Networks. EE381K-14 MDDSP Literary Survey Presentation March 4 th , 2008. By: Wael Barakat Rabih Saliba. Introduction to Data Acquisition. Shannon/Nyquist Sampling Theorem

473 views • 12 slides