User:Dg - Revision history

Dg: /* Week 4: Results of MATLAB Model */

2009-06-23T07:37:05Z

‎Week 4: Results of MATLAB Model

Dg: /* Week 4: Results of MATLAB Model */

2009-06-23T07:32:17Z

‎Week 4: Results of MATLAB Model

Dg at 07:16, 23 June 2009

2009-06-23T07:16:48Z

Dg: /* Week 3: MATLAB Modelling */

2009-06-17T06:54:18Z

‎Week 3: MATLAB Modelling

Dg at 23:47, 16 June 2009

2009-06-16T23:47:29Z

Dg: /* Week 1: Initial Approach */

2009-06-01T11:07:39Z

‎Week 1: Initial Approach

Dg: /* Week 1: Initial Approach */

2009-06-01T09:59:07Z

‎Week 1: Initial Approach

Dg at 09:56, 1 June 2009

2009-06-01T09:56:49Z

Dg at 09:56, 1 June 2009

2009-06-01T09:56:05Z

Dg: /* Initial Approach */

2009-06-01T09:53:41Z

‎Initial Approach

← Older revision		Revision as of 07:37, 23 June 2009
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	I will continue with these tests, exploring how capable this approach is when correcting combinations of slants and tilts. Next I will conduct further tests on images. If successful, I will begin to place function prototypes for these transformations in my branch with the intermediate goal of creating the functions necessary to slant a panorama in Panotools by adjusting a command line parameter.		I will continue with these tests, exploring how capable this approach is when correcting combinations of slants and tilts. Next I will conduct further tests on images. If successful, I will begin to place function prototypes for these transformations in my branch with the intermediate goal of creating the functions necessary to slant a panorama in Panotools by adjusting a command line parameter.

−	[[File:~~Slant example~~.jpg]]	+	http://wiki.panotools.org/File:Slant_example.jpg

← Older revision		Revision as of 07:32, 23 June 2009
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	=Week 4: Results of MATLAB Model=		=Week 4: Results of MATLAB Model=
		+	I've been testing a model in MATLAB for straightening slanted or tilted images. I have parameterized these geometric transformations as angular rotations about the y-axis for slant and x-axis for tilt.
		+
		+	As the attached document shows, simple matrix transformations straighten the slanted image plane so it lies parallel to the x-y plane. As the MATLAB code uploaded to my branch shows, this process is reversible when run on a set of points forming the corners of a square (and its center). The recovered points are exactly equal to the original points. (See Figure 1, if you run the mosaic_v11.m script)
		+
		+	I will continue with these tests, exploring how capable this approach is when correcting combinations of slants and tilts. Next I will conduct further tests on images. If successful, I will begin to place function prototypes for these transformations in my branch with the intermediate goal of creating the functions necessary to slant a panorama in Panotools by adjusting a command line parameter.
		+
	[[File:Slant example.jpg]]		[[File:Slant example.jpg]]

← Older revision		Revision as of 07:16, 23 June 2009
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	I plan to create diagrams illustrating this approach, but they are quite time-consuming to draw in Illustrator, so at the moment, my time is best spent coding and going off of hand-drawn sketches.		I plan to create diagrams illustrating this approach, but they are quite time-consuming to draw in Illustrator, so at the moment, my time is best spent coding and going off of hand-drawn sketches.
		+
		+	=Week 4: Results of MATLAB Model=
		+	[[File:Slant example.jpg]]

@@ Line 112: / Line 112: @@
 Because the image plane is located some distance from the center of projection, it's not easy to rotate about the x- or y-axis while centered at the LookAtPoint.  So to implement the slant and tilt with straightforward matrix transformations, I have described them as a series of rotations and translations of the image plane.
-The next step is to test if this series of transformations effectively causes images taken from what I called "Physical Camera 2" in the [diagram[http://wiki.panotools.org/File:Diagram.png]] to appear as if they are viewed from the "Anchor Camera".  I have a checkerboard surface that I plan to use as a sample planar object.  MATLAB has image transformation functions that will allow me to easily test and view the effects of the image transformations I develop.
+The next step is to test if this series of transformations effectively causes images taken from what I called "Physical Camera 2" in the diagram[http://wiki.panotools.org/File:Diagram.png] to appear as if they are viewed from the "Anchor Camera".  I have a checkerboard surface that I plan to use as a sample planar object.  MATLAB has image transformation functions that will allow me to easily test and view the effects of the image transformations I develop.
 I plan to create diagrams illustrating this approach, but they are quite time-consuming to draw in Illustrator, so at the moment, my time is best spent coding and going off of hand-drawn sketches.

← Older revision		Revision as of 23:47, 16 June 2009
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	Next, the additional parameters added will be optimized. It is unknown whether this optimization will be successful or stable at this point.		Next, the additional parameters added will be optimized. It is unknown whether this optimization will be successful or stable at this point.
		+
		+	=Week 2: Understanding Panotools=
		+	This week, I've been going through filter.h and adjust.c, the two files that contain much of the code to setup transformations. I have added extensive comments to note my understanding of the code and uploaded the results to my branch. Between this detailed reading and review of some older communication on the hugin-ptx list,
		+
		+	http://groups.google.com/group/hugin-ptx/browse_thread/thread/c01fb82c91c7e502/d88a617e1860b691
		+
		+	http://groups.google.com/group/hugin-ptx/browse_thread/thread/cd5806ebee2b09fa/46d07881d7f55adf#46d07881d7f55adf
		+
		+	I feel I have a much better understanding of the current model in panotools. I am working on a list of questions I plan to send to the mailing list over the weekend. Hopefully the answers will clear up the points that I'm still confused on.
		+
		+	From my talk with Daniel this week, I realized my most immediate task is to nail down which additional parameters will describe views captured from non-overhead viewpoints best. While Pablo's suggestion of having an x,y,z coordinate for each image is possible, I have been considering alternate descriptions such as the tilt and slant and distance of an image from a non-overhead view. I need to decide how to precisely define these parameters and which set will best model our system.
		+
		+
		+	=Week 3: MATLAB Modelling=
		+	This past week, I have started developing and testing my geometric model for remapping in MATLAB. Specifically, I have described the position of the plane with the parameters LookAtPoint, tilt, slant, and spin as follows:
		+
		+	* LookAtPoint is the point where a ray exiting the camera's center of projection intersects the image plane.
		+	* tilt is a rotation about the x-axis centered at the LookAtPoint.
		+	* slant is a rotation about the y-axis centered at the LookAtPoint.
		+	* spin is a rotation about the LookAtPoint.
		+
		+	Because the image plane is located some distance from the center of projection, it's not easy to rotate about the x- or y-axis while centered at the LookAtPoint. So to implement the slant and tilt with straightforward matrix transformations, I have described them as a series of rotations and translations of the image plane.
		+
		+	The next step is to test if this series of transformations effectively causes images taken from what I called "Physical Camera 2" in the [diagram[http://wiki.panotools.org/File:Diagram.png]] to appear as if they are viewed from the "Anchor Camera". I have a checkerboard surface that I plan to use as a sample planar object. MATLAB has image transformation functions that will allow me to easily test and view the effects of the image transformations I develop.
		+
		+	I plan to create diagrams illustrating this approach, but they are quite time-consuming to draw in Illustrator, so at the moment, my time is best spent coding and going off of hand-drawn sketches.

← Older revision		Revision as of 11:07, 1 June 2009
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	* We must map from the plane to Physical Camera 2. This gives us a relation between pixels on the plane and the position of Physical Camera 2.		* We must map from the plane to Physical Camera 2. This gives us a relation between pixels on the plane and the position of Physical Camera 2.
		+
		+	Next, the additional parameters added will be optimized. It is unknown whether this optimization will be successful or stable at this point.

@@ Line 77: / Line 77: @@
 =Week 1: Initial Approach=
-Below, we see a top view of the planar object we wish to image.  The circle represents the panosphere and the triangles represent the viewing frusta of two cameras.  We wish to project points on the planar object, (p(x,y)), as viewed from Physical Camera 2 to a virtual (output) Anchor Camera, coincident with Physical Camera 1.
+Below, we see a top view of the planar object we wish to image.  The circle represents the panosphere and the triangles represent the viewing frusta of two cameras.  We wish to project points on the planar object, p(x,y), as viewed from Physical Camera 2 to a virtual (output) Anchor Camera, coincident with Physical Camera 1.
 [[File:Diagram.png]]

@@ Line 73: / Line 73: @@
 •	Richard Szeliski (2006) Image alignment and stitching: a tutorial. Now Publishers Inc.
-********End of Proposal
+* End of Proposal
-=Initial Approach=
+=Week 1: Initial Approach=
 Below, we see a top view of the planar object we wish to image.  The circle represents the panosphere and the triangles represent the viewing frusta of two cameras.  We wish to project points on the planar object, (p(x,y)), as viewed from Physical Camera 2 to a virtual (output) Anchor Camera, coincident with Physical Camera 1.

@@ Line 82: / Line 82: @@
 Creating the output image takes two steps:
-* We must map from the Anchor Camera onto the plane.  This gives us a correspondence between pixels on the plane to angles on the panosphere.
+* We must map from the Anchor Camera onto the plane.  This gives us a relation between angles on the panosphere and pixels on the plane .
-* We must map from the plane to Physical Camera 2.
+* We must map from the plane to Physical Camera 2.  This gives us a relation between pixels on the plane and the position of Physical Camera 2.