In geometry, an affine transformation, affine map or an affinity (from the Latin, affinis, "connected with") is a function between affine spaces which preserves points, straight lines and planes. Also, sets of parallel lines remain parallel after an affine transformation. An affine transformation does not necessarily preserve angles between lines or distances between points, though it does preserve ratios of distances between points lying on a straight line.
If and are affine spaces, then every affine transformation is of the form , where is a linear transformation on and is a vector in . Unlike a purely linear transformation, an affine map need not preserve the zero point in a linear space. Thus, every linear transformation is affine, but not every affine transformation is linear.
Equivalent to a 50 minute university lecture on affine transformations.
0:00 - intro
0:44 - scale
0:56 - reflection
1:06 - shear
1:21 - rotation
2:40 - 3D scale and shear
3:08 - 3D rotations
3:36 - translations
4:23 - 2D translation = 3D shear
5:12 - homogeneous coordinates
Graphics in 5 minutes is a series of cartoon-style videos that teach computer graphics in 10x less time. You can take the equivalent of a University level computer graphics course in just over two hours. The playlist is here:
https://www.youtube.com/playlist?list=PLWfDJ5nla8UpwShx-lzLJqcp575fKpsSO
See here for more information: https://g5m.cs.washington.edu/
published: 02 Jun 2022
Affine Transformations
This video is part of the Udacity course "Computational Photography". Watch the full course at https://www.udacity.com/course/ud955
published: 23 Feb 2015
Affine Transformation
Subscribe To My Channel https://www.youtube.com/@huseyin_ozdemir?sub_confirmation=1
Video Contents:
00:00 Pixel, Pixel Coordinates and Geometric Transformation
01:36 Linear Transformation and Its Properties
02:28 Linear Transform as Matrix-Vector Product
03:21 Affine Transformation
03:46 Comparison of Affine and Linear Transformations
04:38 Affine Transform as Matrix-Vector Product
05:24 Properties of Affine Transformation
05:49 Homogeneous Coordinates
08:29 Intuitive Explanation of Affine Transformation
09:25 Geometric Interpretation of Image Translation as Shear in 3D
* Pixel, Pixel Coordinates and Geometric Transformation
* Linear Transformation and Its Properties
* Linear Transform as Matrix-Vector Product
* Affine Transformation
* Comparison of Affine and Linear Transformations
* Af...
published: 06 Nov 2022
3 1 Affine transformation
GATE Insights Version: CSE
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or
GATE Insights Version: CSE
https://www.youtube.com/channel/UCD0Gjdz157FQalNfUO8ZnNg?sub_confirmation=1
Planning to take coaching on https://unacademy.com/
here is a code for 10% off PLUS1BPK1
Link for our website and app where u can get the pdfs
https://play.google.com/store/apps/details?id=net.itsTimeforFunITF.education4fun
https://education4fun.com/
Ultra Fast and Temp access
http://bit.ly/lets_clear_it
Sem 8 Notes
https://bit.ly/cse-sem-8
Still Confused DM me on WhatsApp
(*Only WhatsApp messages* calls will not be lifted)
Affine Transformation on Images - Rotation, Reflection and Shearing
Lecture on Affine Transformations on the Image such as Rotation, Reflection and Shearing
published: 07 Sep 2021
Affine Transformations — Topic 27 of Machine Learning Foundations
In this video we use hands-on code demos in NumPy to carry out affine transformations, a particular type of matrix transformation that may adjust angles or distances between vectors, but preserves parallelism. These operations can transform the target tensor in a variety of ways including scaling, shearing, or rotation. Affine transformations are also key to appreciating eigenvectors and eigenvalues, the focus of the next videos in the series.
There are eight subjects covered comprehensively in the ML Foundations series and this video is from the second subject, "Linear Algebra II: Matrix Operations". More detail about the series and all of the associated open-source code is available at github.com/jonkrohn/ML-foundations
The next video in the series is: youtu.be/AeIttlCdFXU
The next v...
published: 26 Feb 2021
[MVT#009] Affine transformations
Mechanical vibrations - video tutorial.
A topic of the lecture: Affine transformations.
Instructor: Bogumił Chiliński.
published: 27 Mar 2019
Affine transformation | meaning of Affine transformation
Equivalent to a 50 minute university lecture on affine transformations.
0:00 - intro
0:44 - scale
0:56 - reflection
1:06 - shear
1:21 - rotation
2:40 - 3D scal...
Equivalent to a 50 minute university lecture on affine transformations.
0:00 - intro
0:44 - scale
0:56 - reflection
1:06 - shear
1:21 - rotation
2:40 - 3D scale and shear
3:08 - 3D rotations
3:36 - translations
4:23 - 2D translation = 3D shear
5:12 - homogeneous coordinates
Graphics in 5 minutes is a series of cartoon-style videos that teach computer graphics in 10x less time. You can take the equivalent of a University level computer graphics course in just over two hours. The playlist is here:
https://www.youtube.com/playlist?list=PLWfDJ5nla8UpwShx-lzLJqcp575fKpsSO
See here for more information: https://g5m.cs.washington.edu/
Equivalent to a 50 minute university lecture on affine transformations.
0:00 - intro
0:44 - scale
0:56 - reflection
1:06 - shear
1:21 - rotation
2:40 - 3D scale and shear
3:08 - 3D rotations
3:36 - translations
4:23 - 2D translation = 3D shear
5:12 - homogeneous coordinates
Graphics in 5 minutes is a series of cartoon-style videos that teach computer graphics in 10x less time. You can take the equivalent of a University level computer graphics course in just over two hours. The playlist is here:
https://www.youtube.com/playlist?list=PLWfDJ5nla8UpwShx-lzLJqcp575fKpsSO
See here for more information: https://g5m.cs.washington.edu/
Subscribe To My Channel https://www.youtube.com/@huseyin_ozdemir?sub_confirmation=1
Video Contents:
00:00 Pixel, Pixel Coordinates and Geometric Transformation...
Subscribe To My Channel https://www.youtube.com/@huseyin_ozdemir?sub_confirmation=1
Video Contents:
00:00 Pixel, Pixel Coordinates and Geometric Transformation
01:36 Linear Transformation and Its Properties
02:28 Linear Transform as Matrix-Vector Product
03:21 Affine Transformation
03:46 Comparison of Affine and Linear Transformations
04:38 Affine Transform as Matrix-Vector Product
05:24 Properties of Affine Transformation
05:49 Homogeneous Coordinates
08:29 Intuitive Explanation of Affine Transformation
09:25 Geometric Interpretation of Image Translation as Shear in 3D
* Pixel, Pixel Coordinates and Geometric Transformation
* Linear Transformation and Its Properties
* Linear Transform as Matrix-Vector Product
* Affine Transformation
* Comparison of Affine and Linear Transformations
* Affine Transform as Matrix-Vector Product
* Properties of Affine Transformation
* Homogeneous Coordinates
* Affine Transform in Homogeneous Coordinates
* Intuitive Explanation of Affine Transformation
* Geometric Interpretation of Image Translation as Shear in 3D
All images and animations in this video belong to me
#machinelearning #computervision
#deeplearning #ai #aitutorial #education
#imagetransform #imagelineartransform
#geometrictransform #imagegeometrictransform
#affinetransform #imageaffinetransform
#lineartransform #transformmatrix
#imagerotation #imageflip #imagescaling
#imageshear #imagetranslation
#homogeneouscoordinates
#imageprocessing #datascience
#computervisionwithhuseyinozdemir
Subscribe To My Channel https://www.youtube.com/@huseyin_ozdemir?sub_confirmation=1
Video Contents:
00:00 Pixel, Pixel Coordinates and Geometric Transformation
01:36 Linear Transformation and Its Properties
02:28 Linear Transform as Matrix-Vector Product
03:21 Affine Transformation
03:46 Comparison of Affine and Linear Transformations
04:38 Affine Transform as Matrix-Vector Product
05:24 Properties of Affine Transformation
05:49 Homogeneous Coordinates
08:29 Intuitive Explanation of Affine Transformation
09:25 Geometric Interpretation of Image Translation as Shear in 3D
* Pixel, Pixel Coordinates and Geometric Transformation
* Linear Transformation and Its Properties
* Linear Transform as Matrix-Vector Product
* Affine Transformation
* Comparison of Affine and Linear Transformations
* Affine Transform as Matrix-Vector Product
* Properties of Affine Transformation
* Homogeneous Coordinates
* Affine Transform in Homogeneous Coordinates
* Intuitive Explanation of Affine Transformation
* Geometric Interpretation of Image Translation as Shear in 3D
All images and animations in this video belong to me
#machinelearning #computervision
#deeplearning #ai #aitutorial #education
#imagetransform #imagelineartransform
#geometrictransform #imagegeometrictransform
#affinetransform #imageaffinetransform
#lineartransform #transformmatrix
#imagerotation #imageflip #imagescaling
#imageshear #imagetranslation
#homogeneouscoordinates
#imageprocessing #datascience
#computervisionwithhuseyinozdemir
GATE Insights Version: CSE
http://bit.ly/gate_insights
or
GATE Insights Version: CSE
https://www.youtube.com/channel/UCD0Gjdz157FQalNfUO8ZnNg?sub_confirmation=1
Planning to take coaching on https://unacademy.com/
here is a code for 10% off PLUS1BPK1
Link for our website and app where u can get the pdfs
https://play.google.com/store/apps/details?id=net.itsTimeforFunITF.education4fun
https://education4fun.com/
Ultra Fast and Temp access
http://bit.ly/lets_clear_it
Sem 8 Notes
https://bit.ly/cse-sem-8
Still Confused DM me on WhatsApp
(*Only WhatsApp messages* calls will not be lifted)
GATE Insights Version: CSE
http://bit.ly/gate_insights
or
GATE Insights Version: CSE
https://www.youtube.com/channel/UCD0Gjdz157FQalNfUO8ZnNg?sub_confirmation=1
Planning to take coaching on https://unacademy.com/
here is a code for 10% off PLUS1BPK1
Link for our website and app where u can get the pdfs
https://play.google.com/store/apps/details?id=net.itsTimeforFunITF.education4fun
https://education4fun.com/
Ultra Fast and Temp access
http://bit.ly/lets_clear_it
Sem 8 Notes
https://bit.ly/cse-sem-8
Still Confused DM me on WhatsApp
(*Only WhatsApp messages* calls will not be lifted)
In this video we use hands-on code demos in NumPy to carry out affine transformations, a particular type of matrix transformation that may adjust angles or dist...
In this video we use hands-on code demos in NumPy to carry out affine transformations, a particular type of matrix transformation that may adjust angles or distances between vectors, but preserves parallelism. These operations can transform the target tensor in a variety of ways including scaling, shearing, or rotation. Affine transformations are also key to appreciating eigenvectors and eigenvalues, the focus of the next videos in the series.
There are eight subjects covered comprehensively in the ML Foundations series and this video is from the second subject, "Linear Algebra II: Matrix Operations". More detail about the series and all of the associated open-source code is available at github.com/jonkrohn/ML-foundations
The next video in the series is: youtu.be/AeIttlCdFXU
The next video in the series will be published shortly and the playlist for the entire series is here: youtube.com/playlist?list=PLRDl2inPrWQW1QSWhBU0ki-jq_uElkh2a
This course is a distillation of my decade-long experience working as a machine learning and deep learning scientist, including lecturing at New York University and Columbia University, and offering my deep learning curriculum at the New York City Data Science Academy. Information about my other courses and content is at jonkrohn.com
Dr. Jon Krohn is Chief Data Scientist at untapt, and the #1 Bestselling author of Deep Learning Illustrated, an interactive introduction to artificial neural networks. To keep up with the latest from Jon, sign up for his newsletter at jonkrohn.com, follow him on Twitter @JonKrohnLearns, and on LinkedIn at linkedin.com/in/jonkrohn
In this video we use hands-on code demos in NumPy to carry out affine transformations, a particular type of matrix transformation that may adjust angles or distances between vectors, but preserves parallelism. These operations can transform the target tensor in a variety of ways including scaling, shearing, or rotation. Affine transformations are also key to appreciating eigenvectors and eigenvalues, the focus of the next videos in the series.
There are eight subjects covered comprehensively in the ML Foundations series and this video is from the second subject, "Linear Algebra II: Matrix Operations". More detail about the series and all of the associated open-source code is available at github.com/jonkrohn/ML-foundations
The next video in the series is: youtu.be/AeIttlCdFXU
The next video in the series will be published shortly and the playlist for the entire series is here: youtube.com/playlist?list=PLRDl2inPrWQW1QSWhBU0ki-jq_uElkh2a
This course is a distillation of my decade-long experience working as a machine learning and deep learning scientist, including lecturing at New York University and Columbia University, and offering my deep learning curriculum at the New York City Data Science Academy. Information about my other courses and content is at jonkrohn.com
Dr. Jon Krohn is Chief Data Scientist at untapt, and the #1 Bestselling author of Deep Learning Illustrated, an interactive introduction to artificial neural networks. To keep up with the latest from Jon, sign up for his newsletter at jonkrohn.com, follow him on Twitter @JonKrohnLearns, and on LinkedIn at linkedin.com/in/jonkrohn
Equivalent to a 50 minute university lecture on affine transformations.
0:00 - intro
0:44 - scale
0:56 - reflection
1:06 - shear
1:21 - rotation
2:40 - 3D scale and shear
3:08 - 3D rotations
3:36 - translations
4:23 - 2D translation = 3D shear
5:12 - homogeneous coordinates
Graphics in 5 minutes is a series of cartoon-style videos that teach computer graphics in 10x less time. You can take the equivalent of a University level computer graphics course in just over two hours. The playlist is here:
https://www.youtube.com/playlist?list=PLWfDJ5nla8UpwShx-lzLJqcp575fKpsSO
See here for more information: https://g5m.cs.washington.edu/
Subscribe To My Channel https://www.youtube.com/@huseyin_ozdemir?sub_confirmation=1
Video Contents:
00:00 Pixel, Pixel Coordinates and Geometric Transformation
01:36 Linear Transformation and Its Properties
02:28 Linear Transform as Matrix-Vector Product
03:21 Affine Transformation
03:46 Comparison of Affine and Linear Transformations
04:38 Affine Transform as Matrix-Vector Product
05:24 Properties of Affine Transformation
05:49 Homogeneous Coordinates
08:29 Intuitive Explanation of Affine Transformation
09:25 Geometric Interpretation of Image Translation as Shear in 3D
* Pixel, Pixel Coordinates and Geometric Transformation
* Linear Transformation and Its Properties
* Linear Transform as Matrix-Vector Product
* Affine Transformation
* Comparison of Affine and Linear Transformations
* Affine Transform as Matrix-Vector Product
* Properties of Affine Transformation
* Homogeneous Coordinates
* Affine Transform in Homogeneous Coordinates
* Intuitive Explanation of Affine Transformation
* Geometric Interpretation of Image Translation as Shear in 3D
All images and animations in this video belong to me
#machinelearning #computervision
#deeplearning #ai #aitutorial #education
#imagetransform #imagelineartransform
#geometrictransform #imagegeometrictransform
#affinetransform #imageaffinetransform
#lineartransform #transformmatrix
#imagerotation #imageflip #imagescaling
#imageshear #imagetranslation
#homogeneouscoordinates
#imageprocessing #datascience
#computervisionwithhuseyinozdemir
GATE Insights Version: CSE
http://bit.ly/gate_insights
or
GATE Insights Version: CSE
https://www.youtube.com/channel/UCD0Gjdz157FQalNfUO8ZnNg?sub_confirmation=1
Planning to take coaching on https://unacademy.com/
here is a code for 10% off PLUS1BPK1
Link for our website and app where u can get the pdfs
https://play.google.com/store/apps/details?id=net.itsTimeforFunITF.education4fun
https://education4fun.com/
Ultra Fast and Temp access
http://bit.ly/lets_clear_it
Sem 8 Notes
https://bit.ly/cse-sem-8
Still Confused DM me on WhatsApp
(*Only WhatsApp messages* calls will not be lifted)
In this video we use hands-on code demos in NumPy to carry out affine transformations, a particular type of matrix transformation that may adjust angles or distances between vectors, but preserves parallelism. These operations can transform the target tensor in a variety of ways including scaling, shearing, or rotation. Affine transformations are also key to appreciating eigenvectors and eigenvalues, the focus of the next videos in the series.
There are eight subjects covered comprehensively in the ML Foundations series and this video is from the second subject, "Linear Algebra II: Matrix Operations". More detail about the series and all of the associated open-source code is available at github.com/jonkrohn/ML-foundations
The next video in the series is: youtu.be/AeIttlCdFXU
The next video in the series will be published shortly and the playlist for the entire series is here: youtube.com/playlist?list=PLRDl2inPrWQW1QSWhBU0ki-jq_uElkh2a
This course is a distillation of my decade-long experience working as a machine learning and deep learning scientist, including lecturing at New York University and Columbia University, and offering my deep learning curriculum at the New York City Data Science Academy. Information about my other courses and content is at jonkrohn.com
Dr. Jon Krohn is Chief Data Scientist at untapt, and the #1 Bestselling author of Deep Learning Illustrated, an interactive introduction to artificial neural networks. To keep up with the latest from Jon, sign up for his newsletter at jonkrohn.com, follow him on Twitter @JonKrohnLearns, and on LinkedIn at linkedin.com/in/jonkrohn
In geometry, an affine transformation, affine map or an affinity (from the Latin, affinis, "connected with") is a function between affine spaces which preserves points, straight lines and planes. Also, sets of parallel lines remain parallel after an affine transformation. An affine transformation does not necessarily preserve angles between lines or distances between points, though it does preserve ratios of distances between points lying on a straight line.
If and are affine spaces, then every affine transformation is of the form , where is a linear transformation on and is a vector in . Unlike a purely linear transformation, an affine map need not preserve the zero point in a linear space. Thus, every linear transformation is affine, but not every affine transformation is linear.