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Monthly Archives: July 2010

Difference between SCIE and SciSearch

I just heard SciSearch is another name of SCIE and found the following site which is Korean though.

http://legoman.tistory.com/35

Anyway SciSearch is an online form of SCIE.

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Posted by on July 29, 2010 in Misc

 

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Gaussian Processes for Machine Learning

http://gaussianprocess.org/gpml

Good place where you can download Rasmussen’s book and related Matlab source codes for free.

 
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Posted by on July 24, 2010 in Machine Learning

 

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Arnetminer

This seems a pretty nice site of academic social networks

I found me and other colleague’s names in a graphical form on this site.

Following is the example for Andrew Blake.

http://www.arnetminer.org/viewperson.do?naid=984684&name=Andrew%20Blake

 
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Posted by on July 24, 2010 in Misc

 

Problems with solvePnP

scrapped from : http://tech.groups.yahoo.com/group/OpenCV/message/72678

Re: Problems with solvePnP

I have tried using both “cvFindExtrinsicCameraParams2()” from the C interface
and “solvePnP()” from the C++ interface, because I wasn’t sure of the
difference. I found out that they are exactly the same (it would be good if this
was mentioned in the documentation!), but if you use floating-point values for
the outputs of solvePnP instead of doubles, then it gives extremely large or
extremely small results, just like you guys noticed.

Can someone please update the official C++ documentation to say that
cv::solvePnP() is the C++ equivalent to cvFindExtrinsicCameraParams2(), and that
the rotation & translation outputs should be doubles instead of floats?
(Assuming this is not considered a bug).

The outputs I get on OpenCV 2.0.0 with VS2008 on 32-bit WinXP is shown below.
Notice that the results are all identical between tests (give or take 0.0001%)
except for the last test of solvePnP() with floats.

###### Using <double> cvFindExtrinsicCameraParams2(): ####
Rotation Axis: 0.717367, 0.954479, 0.198497.
Angle: 1.21039 radians (69.3503 deg).
Translation Vector: 324.518, 52.6191, 591.712

###### Using <double> cv::solvePnP(): #####################
Rotation Axis: 0.717367, 0.954479, 0.198497.
Angle: 1.21039 radians (69.3503 deg).
Translation Vector: 324.518, 52.6191, 591.712

###### Using <float> cvFindExtrinsicCameraParams2(): ######
Rotation Axis: 0.717366, 0.954479, 0.198497.
Angle: 1.21039 radians (69.3503 deg).
Translation Vector: 324.518, 52.6191, 591.712

###### Using <float> cv::solvePnP(): ######################
Rotation Axis: -2.1e-032, 1.804, 2.6e+008.
Angle: 2.6e+008 radians (1.5e+010 deg).
Translation Vector: -1.09e-010, 3.81691, -2.82e-039

Cheers,
Shervin Emami.

 
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Posted by on July 23, 2010 in Computer Vision, OpenCV, Programming

 

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analytics1305

machine learning library.

Seems like the source codes are not provided…

Why the name 1305?

http://www.analytics1305.com/

 
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Posted by on July 22, 2010 in Machine Learning

 

openCV video capture properties

OpenCV 1.0

#define CV_CAP_PROP_POS_MSEC       0
#define CV_CAP_PROP_POS_FRAMES     1
#define CV_CAP_PROP_POS_AVI_RATIO  2
#define CV_CAP_PROP_FRAME_WIDTH    3
#define CV_CAP_PROP_FRAME_HEIGHT   4
#define CV_CAP_PROP_FPS            5
#define CV_CAP_PROP_FOURCC         6
#define CV_CAP_PROP_FRAME_COUNT    7
#define CV_CAP_PROP_FORMAT         8
#define CV_CAP_PROP_MODE           9
#define CV_CAP_PROP_BRIGHTNESS    10
#define CV_CAP_PROP_CONTRAST      11
#define CV_CAP_PROP_SATURATION    12
#define CV_CAP_PROP_HUE           13
#define CV_CAP_PROP_GAIN          14
#define CV_CAP_PROP_CONVERT_RGB   15

OpenCV 2.0 (three more options than 1.0)

#define CV_CAP_PROP_POS_MSEC       0
#define CV_CAP_PROP_POS_FRAMES     1
#define CV_CAP_PROP_POS_AVI_RATIO  2
#define CV_CAP_PROP_FRAME_WIDTH    3
#define CV_CAP_PROP_FRAME_HEIGHT   4
#define CV_CAP_PROP_FPS            5
#define CV_CAP_PROP_FOURCC         6
#define CV_CAP_PROP_FRAME_COUNT    7
#define CV_CAP_PROP_FORMAT         8
#define CV_CAP_PROP_MODE           9
#define CV_CAP_PROP_BRIGHTNESS    10
#define CV_CAP_PROP_CONTRAST      11
#define CV_CAP_PROP_SATURATION    12
#define CV_CAP_PROP_HUE           13
#define CV_CAP_PROP_GAIN          14
#define CV_CAP_PROP_EXPOSURE      15
#define CV_CAP_PROP_CONVERT_RGB   16
#define CV_CAP_PROP_WHITE_BALANCE 17
#define CV_CAP_PROP_RECTIFICATION 18

 
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Posted by on July 20, 2010 in OpenCV, Programming

 

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Free SIFT / SURF alternatives

Scrapped from http://tech.groups.yahoo.com/group/OpenCV/message/72592

I’ve tested the SIFT/SURF alternatives mentioned in a post by Gary last year and found them lacking.

FAST detector for keypoints – does not characterize keypoints (it’s fast, though)

Self-similarity features for keypoints (code by Rainer Lienhart) is IMHO patented by Shechtman & Irani as US patent (application), see e.g. http://www.faqs.org/patents/app/20100104158 (IMHO the US patent office allows to put in patents up to one year after publication)

Fast Keypoint Recognition using Random Ferns – similar speed and accuracy as SIFT/SURF, but needs far too much memory. I’ve measured 500M per object recognized even after optimizing the parameters in find_obj_ferns.cpp to reduce memory requirements. IMHO it does not make sense to train one fern classifier on multiple keypoints from the same object so this memory footprint would be incurred for each object to be recognized. E.g. to recognize 76 magazine pages like here (video done by myself), you’d need a whooping 34TB of main memory – not feasible.

http://www.youtube.com/user/SeewaldSolutions#p/f/3/1QceIPixocw

Given that cvSURF works reasonably well on small devices (I made it to about 1 fps on a recent Android model), which have nowhere that much memory, I currently don’t see any _feasible_ alternatives to SIFT/SURF for large-scale object recognition in OpenCV. Any idea/pointers? What can I do to fix this?

 
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Posted by on July 20, 2010 in Computer Vision, OpenCV

 

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