CSCE 5013
Computer Vision
Fall 2011
Prof. John Gauch
jgauch@uark.edu
Ch1 - Introduction
Overview
Application Areas
History
Course Objectives
Overview
Computer vision is the process of extracting
useful information from digital images
Finding objects of
Introduction to Computer Vision
Michael J. Black
Nov 2009
Stereo
CS143 Intro to Computer Vision
Michael J. Black
Goals
Today
Binocular stereo
Friday
Either object recognition or human shape and
pose.
CS143 Intro to Computer Vision
Michael J. Black
CS1
Sample Computer Vision Questions
Block World Models
Suppose you asked are to build a computer vision demonstration system for a children's museum.
The idea is to have a "playroom" with a variety of building blocks and have a computer
controlled robot arm
Ch10 Segmentation
Overview
Thresholding
Region Growing
Split and Merge
Watershed Segmentation
Conclusion
Overview
The purpose of segmentation is to divide an
image into visually sensible regions
corresponding to objects of interest
Segmentation is the d
Ch10 Edge Detection
Overview
Edge Models
Edge Detection
Gradient Based
Edge Templates
Laplacian Zero Crossings
Canny Operator
Performance Evaluation
Hough Transform
Conclusion
Overview
The purpose of edge detection is to locate the
boundaries o
Ch 5 - Boundary Models
Overview
Edge Tracking
Active Contours
Conclusion
Introduction
Overview
ppose we wish to find the boundary of an
Suppose we wish to find the boundary of an
ject object image
in an in an image
ne One approach is to find edge segment
Ch 4 - Feature Detection
Overview
Feature Detection
Intensity Extrema
Blob Detection
Corner Detection
Feature Descriptors
Feature Matching
Conclusion
Overview
Goal of feature detection is to find geometric
objects in an image that are visually in
Ch3 Spatial Filtering 2
Overview
Spatial Highpass Filter
Unsharp Masking
Variance Based Enhancement
Wallis Operator
Derivative Filters
Laplacian Filters
Conclusion
Overview
In this section, we focus on techniques that
sharpen images to enhance small deta
Ch3 Spatial Filtering 1
Overview
Correlation and Convolution
Neighborhood Averaging
Binomial Filtering
Gaussian Blurring
Outlier Removal
Median Filtering
k-Nearest Neighbors
Conclusion
Overview
Spatial filters make use of a
fixed sized neighborhood in
an
Ch 3 - Intensity Transformations
Overview
Linear Map
Inverse Map
Thresholding
Windowing
Log Transformation
Power Law
Transformation
Contrast Stretching
Intensity Slicing
Bit Plane Images
Conclusion
Overview
Goal is to modify pixel intensity to impro
Ch2 Image Formation
Overview
Geometric Primitives
2D Geometric Transformations
3D Geometric Transformations
Image Formation
Image Sampling
Conclusions
Overview
Before we can understand how digital images
are formed we must review some geometry
Geometric
Ch1 Object Modeling
Overview
Point Selection
Bounding Box Line Equation
Least Square Line Equation
Conclusions
Overview
Assume that we have an image of a table
How can we create a mathematical model this
geometric object?
Overview
One option is to calc
MCIS 5103 Advanced Programming Concepts
Assignment 5 Case Study Questions Due 10/23/2014
1. What is the difference between domain definition and domain dictionary? Give an example
for each.
ANS:
Domain definition provides a framework for the conceptual su