Upload File

sppra2010 estimating a rotation matrix r by using higher-order matrices r^n with application to...

  • Home
  • Technology
  • SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation
17
Estimating a rotation matrix R by using higher-order matrices R n with application to supervised pose estimation Toru Tamaki Bisser Raytchev Kazufumi Kaneda Toshiyuki Amano

Upload: toru-tamaki

Post on 25-Jun-2015

376 views

Category:

Technology


0 download

Report

Tags:

DESCRIPTION

Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda, Toshiyuki Amano : "Wstimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation," Proc. of SPPRA 2010: The Seventh IASTED International Conference on Signal Processing, Pattern Recognition and Applications, pp. 58-64 (2010 02). Innsbruck, Austria, 2010/February/17-19.

TRANSCRIPT

Page 1: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Estimating a rotation matrix Rby using higher-order matrices Rn

with application tosupervised pose estimation

Toru Tamaki

Bisser Raytchev

Kazufumi Kaneda

Toshiyuki Amano

Page 2: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Estimating a rotation matrix Rby using higher-order matrices Rn

with application tosupervised pose estimation

Toru Tamaki

Bisser Raytchev

Kazufumi Kaneda

Toshiyuki Amano

Can Rn estimate Rmore accurately than R ?

Page 3: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

To  improve  estimates…  Average!

t1

t2

tn

t… …Measure many times

AverageLease-Squares

How improve?

When  measurement  is  only  once…

Page 4: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

To  improve  estimates…  Average!

t1

t2

tn

t… …Measure with many timers

AverageLease-Squares

When  measurement  is  only  once…

Improve!

Page 5: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

To  improve  estimates…  Average?

…

t

t2

tn

…Measure with many timers

When  measurement  is  only  once…

How improve?

t

AverageLease-Squares

Page 6: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

To  improve  estimates…  Average.

t

t2

tn

t… …Measure with many timers

When  measurement  is  only  once…

Improve!

But, What is it?

Page 7: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Our problem: Pose estimation

Pose parameters

Rt

3x3 rotation matrix

3D translation

R

image

R

Regression:Appearance-based / View-based pose estimation

Parametric Eigenspace (Murase et al., 1995)linear regression (Okatani et al., 2000)

kernel CCA (Melzer et al., 2003)SV regression (Ando et al., 2005)

Manifold learning, and others(Rothganger et al., 2006) (Lowe, 2004) (Ferrari et

al., 2006) (Kushal et al., 2006) (Viksten, 2009)

Poseparameters

Page 8: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Our concept

p1 R

Rotationmatrix

Posevectorimage

µ

!1

Training

2µ

!

p2 R22

axis

angle

Page 9: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

! µ

Our concept

p1

Posevector

µ

!

2µ

!

p22

1 R

Rotationmatrix

R2

PolarDecomp.

! µaxis angle

! 2µ

EigenDecomp.

Newimage

axis

angle

Page 10: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Our concept

p1 R ! µ

Rotationmatrix axis angle

Posevector

µ

!

2µ

!

p2 R2 ! 2µ2

1Polar

Decomp.Eigen

Decomp.

! µ

Newimage

29 [deg]

62 [deg]

30 [deg]

Examples

210 [deg]

420 [deg]

? [deg]

31 [deg]

=60 [deg]

30 [deg]Div by 2 Div by 2

axis

angle

Page 11: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Surveying

Surveying – ARCHEOSCANhttp://archeoscan.com/16.html

EDMElectronic Distance Measurement

Page 12: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Principle of EDM

µ2

Dist

µ1

Transmitter Receiver

¸1

¸2

targetdevice

Use•Longer wavelength ¸1 first, for a rough phase estimate µ1•Shorter wavelength ¸2 next, for a fine phase estimate µ2

Page 13: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Our concept

p1 R ! µ

Rotationmatrix axis angle

Posevector

µ

!

2µ

!

p2 R2 ! 2µ2

1Polar

Decomp.Eigen

Decomp.

! µ

Newimage

29 [deg]

62 [deg]

30 [deg]

Examples

210 [deg]

420 [deg]

210 [deg]

31 [deg]

=60 [deg]

210 [deg]Div by 2 Div by 2

Page 14: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Simulation 1

!

µ

R

p1

Posevector

p8

+noise

+noise

… R

Rotationmatrix

R8

PolarDecomp.

… !1 µ1

axis angle

!8 µ8

EigenDecomp.

… …R R

R8

…

Measurements

Page 15: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Simulation 2

p1 R !1 µ1

Rotationmatrix axis angle

Posevector

p8 R8 !8 µ8

PolarDecomp.

EigenDecomp.

!

µ

+noise R

R8

R

… … … … …

Error  doesn’t  change…No free lunch!

R

Measurements

Page 16: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Experimental results

p1 R !1 µ1

Rotationmatrix axis angle

Posevector

p8 R8 !8 µ8

PolarDecomp.

EigenDecomp.

!

µ

R

… … … …1

8

•Linear regression•Training withimages and poses

images

Page 17: SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation

Summary

• Improve estimates of a pose R with many measurements R1, R2,  …,  R8• Simulations and experimental results shows that the concept works!


Weakly Supervised Adversarial Learning for 3D Human Pose ... · the pose prototypes, and then use that representation to estimate the 3D human pose from depth. Though discriminative

Self-Supervised Learning of 3D Human Pose Using Multi-View …openaccess.thecvf.com/content_CVPR_2019/papers/Kocabas... · 2019-06-10 · Self-Supervised Learning of 3D Human Pose

Weakly-supervised 3D Hand Pose Estimation from Monocular ...imi.ntu.edu.sg/NewsEvents/Events/PastSeminars/Documents/31_Jan… · Convolutional Pose Machines [Wei. et al. CVPR 2016]

semi-supervised training - arxiv.org · Semi-supervised training. There has been work on mul-titask networks [3] for joint 2D and 3D pose estimation [36,33] as well as action recognition

BY; KIPLAGAT SHADRACK A22/0074/2009 SUPERVISED BY; DR. R. NYANKANGA

SEED: SELF SUPERVISED DISTILLATION FOR VISUAL R

Improving Temporal Interpolation of Head and Body Pose ...Improving Temporal Interpolation of Head and Body Pose XXX, XXX, 4 METHODOLOGY In the supervised learning se−ing for a linear

6D Object Pose Regression via Supervised Learning on Point Clouds · 2020-01-27 · 6D Object Pose Regression via Supervised Learning on Point Clouds Ge Gao 1, Mikko Lauri , Yulong

¸r(5).pdf · stetoskop tilbehør Beskrivelse Cardiology Il, sort Cardiology Il, grå side 3 Pakning 3 stk/pose 3 stk/pose 3 stk/pose 3 stk/pose Pakning 5 stk/pose 5 stk/pose Pakning

Deep Graph Pose: a semi-supervised deep graphical model ...€¦ · Semi-supervised learning aims to fully utilize unlabeled or weakly-labeled data to gain additional insights into

Weakly-Supervised Discovery of Geometry-Aware ...openaccess.thecvf.com/content_CVPR_2019/papers/Chen...Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose

Onboard and Ground Visual Pose r

SUPERVISED LEARNING MODEL FOR KICKSTARTER CAMPAIGNS WITH R MINING

Real-Time Articulated Hand Pose Estimation Using …Real-time Articulated Hand Pose Estimation using Semi-supervised Transductive Regression Forests Danhang Tang Imperial College London

Tsogt-Ochir Tungalag (L) and Jadambaa Nasanjargal (R) pose

“How to rate a video game?” - A prediction system for ... - arxiv.org · pose a supervised learning technique for summarizing videos by automatically selecting key-frames. They

Weakly-supervised 3D Hand Pose Estimation from Monocular … · 2018-08-28 · 2 Yujun Cai, Liuhao Ge, Jianfei Cai, Junsong Yuan Fig.1.Illustration of the concept of weakly supervised

A Self-supervised Learning System for Object Detection ... · A Self-supervised Learning System for Object Detection using Physics Simulation and Multi-view Pose Estimation Chaitanya

A Supervised Learning Architecture for Human Pose Recognition in a Social Robot

Weakly Supervised Scale-Invariant Learning of …fergus/papers/fergus_ijcv.pdfWeakly Supervised Scale-Invariant Learning of Models for Visual Recognition R. Fergus1 P. Perona2 A. Zisserman1

Multiview-Consistent Semi-Supervised Learning for 3D ......Multiview-Consistent Semi-Supervised Learning for 3D Human Pose Estimation Rahul Mitra∗ IIT Bombay [email protected]

The Holiday Participation Centre, - earth-net · PDF fileThe Holiday Participation Centre . r Overcome barriers duration Individual day trip Group day trip, supervised Supervised group

Weakly-supervised 3D Hand Pose Estimation from Monocular RGB …openaccess.thecvf.com/content_ECCV_2018/papers/Yujun_Cai... · 2018-08-28 · Weakly-supervised 3D HandPose Estimation

Weakly-Supervised 3D Pose Estimation from a …epubs.surrey.ac.uk/852639/1/Weakly-Supervised 3D Pose...More recently, Convolutional Pose Machines have become a popular approach [34]

Multi-view Self-supervised Deep Learning for 6D Pose ... · Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge Andy Zeng 1Kuan-Ting Yu2

john-russell.orgjohn-russell.org/Texts/7op.pdf · ocean pose. ocean pose. cxean pose. ocean pose _ ocean pose. ocean pose. ocean pose. ocean pose. ocean pose starting in the south

Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approachzhouxy/materials/ICCV17... · 2019. 6. 9. · Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised

Time-Contrastive Networks: Self-Supervised … Networks: Self-Supervised Learning from Video ... as pouring are learned by watching a single 3rd-person demon- ... R Google …

USING SUPERVISED DEEP LEARNING FOR HUMAN AGE …...USING SUPERVISED DEEP LEARNING FOR HUMAN AGE ESTIMATION PROBLEM ... which contains 1002 images with a broad variety of light, pose,

Self-Supervised 3D Human Pose Estimation via Part Guided ...Jogendra Nath Kundu 1Siddharth Seth Varun Jampani2 Mugalodi Rakesh R. Venkatesh Babu 1Anirban Chakraborty 1Indian Institute

Weakly Supervised Adversarial Learning for 3D Human Pose ...humanmotion.ict.ac.cn/papers/2019P7_POSE/paper.pdf · weakly supervised adversarial learning framework for 3D human pose

A Robust Likelihood Function for 3D Human Pose Trackingvisal.cs.cityu.edu.hk/static/pubs/journal/tip14-robustlikelihood.pdf · 3 table ii previous work on supervised 3d human pose

Weakly- and Semi-supervised Faster R-CNN with Curriculum ...xinggangw.info/pubs/wasscl-icpr18.pdf · very closing to the fully-supervised Faster R-CNN and its speed is as fast as

Self-Supervised Learning of Pose Embeddings From

Multi-view Self-supervised Deep Learning for 6D … · Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge ... provides speed,