Administrivia. Administrivia. Visual motion. CMPSCI 370: Intro. to Computer Vision. Optical flow

Similar documents
Optical flow. Visual motion. Motion and perceptual organization. Motion and perceptual organization. Subhransu Maji. CMPSCI 670: Computer Vision

Image Registration - Agenda. Image Registration II. Optical Flow. Estimating Optical Flow. Dr. Yossi Rubner

HYPOTHESIS TESTING. four steps

6.2 The Moment-Curvature Equations

Optical flow. Subhransu Maji. CMPSCI 670: Computer Vision. October 20, 2016

Statistical Estimation

Optical flow equation

Additional Tables of Simulation Results

1. Six acceleration vectors are shown for the car whose velocity vector is directed forward. For each acceleration vector describe in words the

Fresnel Dragging Explained

6/10/2014. Definition. Time series Data. Time series Graph. Components of time series. Time series Seasonal. Time series Trend

Stationarity and Unit Root tests

Chapter 9 Autocorrelation

UNIT 1: ANALYTICAL METHODS FOR ENGINEERS

10.3 Autocorrelation Function of Ergodic RP 10.4 Power Spectral Density of Ergodic RP 10.5 Normal RP (Gaussian RP)

2 f(x) dx = 1, 0. 2f(x 1) dx d) 1 4t t6 t. t 2 dt i)

ENGINEERING MECHANICS

Big O Notation for Time Complexity of Algorithms

Section 8. Paraxial Raytracing

1. Solve by the method of undetermined coefficients and by the method of variation of parameters. (4)

STK4080/9080 Survival and event history analysis

O & M Cost O & M Cost

Paper 3A3 The Equations of Fluid Flow and Their Numerical Solution Handout 1

Extremal graph theory II: K t and K t,t

Four equations describe the dynamic solution to RBC model. Consumption-leisure efficiency condition. Consumption-investment efficiency condition

The sphere of radius a has the geographical form. r (,)=(acoscos,acossin,asin) T =(p(u)cos v, p(u)sin v,q(u) ) T.

Chapter 11 Autocorrelation

Numerical KDV equation by the Adomian decomposition method

Solutions to selected problems from the midterm exam Math 222 Winter 2015

λiv Av = 0 or ( λi Av ) = 0. In order for a vector v to be an eigenvector, it must be in the kernel of λi

Localization. MEM456/800 Localization: Bayes Filter. Week 4 Ani Hsieh

FIXED FUZZY POINT THEOREMS IN FUZZY METRIC SPACE

Online Supplement to Reactive Tabu Search in a Team-Learning Problem

Let s express the absorption of radiation by dipoles as a dipole correlation function.

MITPress NewMath.cls LAT E X Book Style Size: 7x9 September 27, :04am. Contents

C(p, ) 13 N. Nuclear reactions generate energy create new isotopes and elements. Notation for stellar rates: p 12

Chemistry 1B, Fall 2016 Topics 21-22

SUMMATION OF INFINITE SERIES REVISITED

Cameras and World Geometry

ANALYSIS OF THE CHAOS DYNAMICS IN (X n,x n+1) PLANE

Four equations describe the dynamic solution to RBC model. Consumption-leisure efficiency condition. Consumption-investment efficiency condition

A Generalized Cost Malmquist Index to the Productivities of Units with Negative Data in DEA

Lecture 15 First Properties of the Brownian Motion

The Nehari Manifold for a Class of Elliptic Equations of P-laplacian Type. S. Khademloo and H. Mohammadnia. afrouzi

AdaBoost. AdaBoost: Introduction

Paraxial ray tracing

Comparison between Fourier and Corrected Fourier Series Methods

ECE 340 Lecture 15 and 16: Diffusion of Carriers Class Outline:

K3 p K2 p Kp 0 p 2 p 3 p

Chapter 6 - Work and Energy

July 24-25, Overview. Why the Reliability Issue is Important? Some Well-known Reliability Measures. Weibull and lognormal Probability Plots

Final Exam Applied Econometrics

Numerical Method for Ordinary Differential Equation

A TAUBERIAN THEOREM FOR THE WEIGHTED MEAN METHOD OF SUMMABILITY

Inference of the Second Order Autoregressive. Model with Unit Roots

Coordinate Systems. Things to think about:

Approximate Solutions for the Coupled Nonlinear. Equations Using the Homotopy Analysis Method

( ) ( ) ( ) ( ) (b) (a) sin. (c) sin sin 0. 2 π = + (d) k l k l (e) if x = 3 is a solution of the equation x 5x+ 12=

On The Geometrıc Interpretatıons of The Kleın-Gordon Equatıon And Solution of The Equation by Homotopy Perturbation Method

Notes 03 largely plagiarized by %khc

th m m m m central moment : E[( X X) ] ( X X) ( x X) f ( x)

Energy Density / Energy Flux / Total Energy in 1D. Key Mathematics: density, flux, and the continuity equation.

The analysis of the method on the one variable function s limit Ke Wu

Moment Generating Function

A Note on Random k-sat for Moderately Growing k

BEST LINEAR FORECASTS VS. BEST POSSIBLE FORECASTS

Math 10B: Mock Mid II. April 13, 2016

Detecting Movement SINA 07/08

Math 6710, Fall 2016 Final Exam Solutions

F D D D D F. smoothed value of the data including Y t the most recent data.

CS623: Introduction to Computing with Neural Nets (lecture-10) Pushpak Bhattacharyya Computer Science and Engineering Department IIT Bombay

Conditional Probability and Conditional Expectation

Principles of Communications Lecture 1: Signals and Systems. Chih-Wei Liu 劉志尉 National Chiao Tung University

CS376 Computer Vision Lecture 6: Optical Flow

t = s D Overview of Tests Two-Sample t-test: Independent Samples Independent Samples t-test Difference between Means in a Two-sample Experiment

Math 2414 Homework Set 7 Solutions 10 Points

VARIATIONAL ITERATION METHOD: A COMPUTATIONAL TOOL FOR SOLVING COUPLED SYSTEM OF NONLINEAR PARTIAL DIFFERENTIAL EQUATIONS

LINEAR APPROXIMATION OF THE BASELINE RBC MODEL SEPTEMBER 17, 2013

6.003: Signals and Systems Lecture 20 April 22, 2010

David Randall. ( )e ikx. k = u x,t. u( x,t)e ikx dx L. x L /2. Recall that the proof of (1) and (2) involves use of the orthogonality condition.

ODEs II, Supplement to Lectures 6 & 7: The Jordan Normal Form: Solving Autonomous, Homogeneous Linear Systems. April 2, 2003

CLOSED FORM EVALUATION OF RESTRICTED SUMS CONTAINING SQUARES OF FIBONOMIAL COEFFICIENTS

Analytical approximate solutions for two-dimensional incompressible Navier-Stokes equations

Velocity is a relative quantity

Curvilinear Motion: Normal and Tangential Components

Vibration damping of the cantilever beam with the use of the parametric excitation

Economics 8723 Macroeconomic Theory Problem Set 3 Sketch of Solutions Professor Sanjay Chugh Spring 2017

EGR 544 Communication Theory

Mixture of a New Integral Transform and Homotopy Perturbation Method for Solving Nonlinear Partial Differential Equations

Page 1. Before-After Control-Impact (BACI) Power Analysis For Several Related Populations. Richard A. Hinrichsen. March 3, 2010

Ideal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory

The need for complex dynamic models

Lecture 15: Three-tank Mixing and Lead Poisoning

CSE 241 Algorithms and Data Structures 10/14/2015. Skip Lists

Pure Math 30: Explained!

CHAPTER 2 TORSIONAL VIBRATIONS

Procedia - Social and Behavioral Sciences 230 ( 2016 ) Joint Probability Distribution and the Minimum of a Set of Normalized Random Variables

OLS bias for econometric models with errors-in-variables. The Lucas-critique Supplementary note to Lecture 17

The modified Exp-function method and its applications to the generalized K(n,n) and BBM equations with variable coefficients

Stable Model for Active Contour based Region Tracking using Level Set PDE

Transcription:

Admiisriia Fial eam: Thrsda, Ma 5, -3pm, Hasbrock 3 Reiew sessio poll Thrsda, April 8, 4-5pm, Locaio: TDB Tesda, Ma 3, 4-5pm, Locaio: TDB CMPSC 370: ro. o Comper Visio Reiew oes are posed o Moodle Opical flow Uiersi of Massachses, Amhers April 6, 06 Hoors secio srcor: Sbhras Maji Toda, 4-5pm 0 mi preseaio Frida, Ma 6, midigh wriep of 4-6 pages Admiisriia Visal moio Coclde deep learig Reiew decisio rees Homework 5 de Thrsda deadlie eeded b das Opical flow SRT forms las 5 mis Need a oleer o ake he forms o he CS mai office? Ma slides adaped from S. Seiz, R. Szeliski, M. Pollefes 3 3 4 4

Moio ad percepal orgaizaio Someimes, moio is he ol ce Moio ad percepal orgaizaio Someimes, moio is he ol ce 5 Moio ad percepal orgaizaio Ee impoerished moio daa ca eoke a srog percep 5 6 Uses of moio Esimaig 3D srcre Segmeig objecs based o moio ces Learig ad rackig damical models Recogizig ees ad aciiies 6 G. Johasso, Visal Percepio of Biological Moio ad a Model For s Aalsis, Percepio ad Pschophsics 4, 0-, 973. 7 8 7 8

Moio field The moio field is he projecio of he 3D scee moio io he image Opical flow Defiiio: opical flow is he appare moio of brighess paers i he image deall, opical flow wold be he same as he moio field Hae o be carefl: appare moio ca be cased b lighig chages wiho a acal moio Thik of a iform roaig sphere der fied lighig s. a saioar sphere der moig illmiaio 9 0 Gie wo sbseqe frames, esimae he appare moio field, ad, bewee hem 9 Esimaig opical flow 0 The brighess cosac cosrai,,,,,,,, Brighess Cosac Eqaio:,, = +,, +,, Ke assmpios Brighess cosac: projecio of he same poi looks he same i eer frame Small moio: pois do o moe er far Spaial coherece: pois moe like heir eighbors Liearizig he righ side sig Talor epasio:,,,, +,, Hece, + + 0 +

The brighess cosac cosrai + + = 0 How ma eqaios ad kows per piel? Oe eqaio, wo kows Wha does his cosrai mea?, + = 0 The compoe of he flow perpediclar o he gradie i.e., parallel o he edge is kow The brighess cosac cosrai + + = 0 How ma eqaios ad kows per piel? Oe eqaio, wo kows Wha does his cosrai mea?, + = 0 The compoe of he flow perpediclar o he gradie i.e., parallel o he edge is kow f, saisfies he eqaio, so does +, + if ', ' = 0 gradie,, +,+ edge 3 The aperre problem 4 The aperre problem Perceied moio Acal moio 5 6 5 6

The barber pole illsio 7 hp://e.wikipedia.org/wiki/barberpole_illsio 7 How o ge more eqaios for a piel? Spaial coherece cosrai: preed he piel s eighbors hae he same, E.g., if we se a 55 widow, ha gies s 5 eqaios per piel Solig he aperre problem 8 0 ], [ = + i i [ Lcas Kaade mehod, 98 ] 8 Leas sqares problem: Solig he aperre problem 9 Whe is his ssem solable? Wha if he widow coais js a sigle sraigh edge? [ Lcas Kaade mehod, 98 ] 9 Bad case: sigle sraigh edge Codiios for solabili 0 0

Good case Codiios for solabili Liear leas sqares problem Lcas-Kaade flow B. Lcas ad T. Kaade. A ieraie image regisraio echiqe wih a applicaio o sereo isio. Proceedigs of he eraioal Joi Coferece o Arificial elligece, pp. 674 679, 98. The smmaios are oer all piels i he widow Solio gie b = b A d b A Ad A T T = Lcas-Kaade flow 3 Recall he Harris corer deecor: M = A T A is he secod mome mari We ca figre o wheher he ssem is solable b lookig a he eigeales of he secod mome mari The eigeecors ad eigeales of M relae o edge direcio ad magide The eigeecor associaed wih he larger eigeale pois i he direcio of fases iesi chage, ad he oher eigeecor is orhogoal o i 3 Visalizaio of secod mome marices 4 4

Visalizaio of secod mome marices erpreig he eigeales Classificaio of image pois sig eigeales of he secod mome mari: λ Edge λ >> λ Corer λ ad λ are large, λ ~ λ λ ad λ are small Fla Edge regio λ >> λ 5 λ 6 5 Eample 6 Uiform regio gradies hae small magide small λ, small λ ssem is ill-codiioed * From Khrram Hassa-Shafiqe CAP545 Comper Visio 0037 8 7 8

Edge High-ere or corer regio gradies hae oe domia direcio large λ, small λ ssem is ill-codiioed gradies hae differe direcios, large magides large λ, large λ ssem is well-codiioed 9 30 9 Opical Flow Resls 30 Errors i Lcas-Kaade The moio is large larger ha a piel eraie refieme Coarse-o-fie esimaio Ehasie eighborhood search feare machig A poi does o moe like is eighbors Moio segmeaio Brighess cosac does o hold Ehasie eighborhood search wih ormalized correlaio * From Khrram Hassa-Shafiqe CAP545 Comper Visio 003 3 3 3 3

Mli-resolio regisraio Opical Flow Resls 33 33 * From Khrram Hassa-Shafiqe CAP545 Comper Visio 003 Opical Flow Resls 34 34 * From Khrram Hassa-Shafiqe CAP545 Comper Visio 003 Sae-of-he-ar opical flow Sar wih somehig similar o Lcas-Kaade + gradie cosac + eerg miimizaio wih smoohig erm + regio ad kepoi machig log-rage Regio-based +Piel-based +Kepoi-based * From Khrram Hassa-Shafiqe CAP545 Comper Visio 003 35 Large displaceme opical flow, Bro e al., CVPR 009 Sorce: J. Has 36 35 36