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SS5305 – Advanced Motion Capture

Tutor: Mr. Owais Malik and Mr. Joko TrilokaRoom No: 2.31

Email: malikowais@yahoo.com

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Objectives

• Human Motion Analysis• Classification of Human Motion• Analysis of Techniques• Hierarchical or Deterministic Models• Dynamical Systems Theory• Conclusions

Human Motion Analysis: Standard Pipeline

Multi-View High-Speed Recording Image Feature Tracking

View 1 View 2

3

1 2

4

2D -> 3D Reconstruction

Camera 1 Camera 1

3D

Kinematic Model Fitting

Definitions: Classifications of Human Motion

– General Motion Patterns (e.g. Jumping)

– Skill (e.g. High Jump)

– Technique (e.g. Fosbury Flop)

– Style (Individual variation in the performance of Technique)

– Primary Motion Analysis Purpose (height of clearance, Objective/Outcome/Performance)

(Kreighbaum & Barthels, 1996)

Variation of Parameters Measured • Approach velocity is a predictor of height

jumped

• Hip height at take off is a predictor of height jumped

• Why do some international high jumpers “buckle” ? (i.e. not even leave the ground)

• Variation

Dapena (1980a and b) Medicine and Science in Sports and Exercise

Factors Affecting “Style”

• Factors Affecting “Style” i.e. constraints– Leg strength and power– Flexibility – Height– Weight– Body composition

– Individual constraints are variable between jumpers– What about variations within a jumper between

attempts?

Dapena (1980a and b) Medicine and Science in Sports and Exercise

Analysis of Techniques

• 3 main steps:observation - several aids developedevaluation - fault diagnosisintervention - poorly address

Observation

• Phase Analysis - descriptive process to divide motion into constituent parts

• Temporal Analysis - builds on phase analysis by specifying the timing of a motion

• Critical Features - components of motion that are essential to the performance of a skill

Evaluation

• Coaching Manuals - descriptive templates based on expert performance

• Diagnosis of faults determined by deviations from the template

• Aware of variations in performance level and individual differences

• Criticisms of this approach based on premise that success and high technical skill have a reciprocal relationship (Hay & Reid, 1982; Bartlett, 2007)

Hierarchical or deterministic models

The model must be based upon governing motion, and each factor must be completely determined by those factors that appear in the level directly below it.(Glazier et al., 2007; Hay & Reid, 1982)

Novel Sprint Running Training(uphill-downhill ramp 3 degree slope)

()

()

()

()

DCM

Hierarchical Model of Sprint Running

DCM TO

Running Speed

Step Length Step Rate

Flight Distance

knee angle ()

Physique

Acceleration (g)

Velocity TD

Force Exerted

DCM TD

Posture

hip angle ()

trunk angle ()

thigh angle ()

shank angle ()

Step Time

Contact Time Flight Time

Eccentric Concentric

Height TO

Air Resistance

Speed TO

Velocity change

Time Forces Act

Paradisis and Cooke (2001) Journal of Sports Sciences

Group changes in max running velocity (MRV)

-0.3-0.2-0.1

00.10.20.30.40.50.6

Training Control

Run

ning

Velo

city

(m.s

-1)

**

**P<0.01

Group changes in stride rate

-0.2

-0.1

0

0.1

0.2

0.3

Training Control

Strid

e Rat

e (H

z)

**

**P<0.01

Individual variation in response to training

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Participants

Po

st-P

re T

rain

ing

Ch

ang

es (

%)

MRV 4.0% 2.4% -1.4% 6.4% 2.4% 3.4% 5.5% 9.1% 11.1% 1.9% 2.5%

SR 3.6% 6.3% 0.0% 3.2% 2.7% 3.5% 3.0% 6.6% 10.2% 0.0% 0.0%

SL 0.5% -3.8% -1.4% 3.2% -0.5% 0.0% 2.3% 2.2% 0.7% 1.9% 2.5%

CT 4.7% 6.7% 6.7% 5.9% 5.6% 6.3% 6.3% 0.0% 0.0% 0.0% 5.9%

FT 2.3% 5.6% -5.9% 0.0% 0.0% 0.0% 0.0% 11.1% 18.8% 0.0% -7.1%

N=10 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10

Improvement

Decline

Dynamical Systems Theory

• Motor control theory that looks at how multiple degrees of freedom are controlled (Utley & Astill, 2008)

• The athlete is considered as a complex, biological system (Davids et al., 2008)

• Consider the system as a whole, where the parts of the system interact and affect each other.

Dynamical Systems Theory (Newell 1986 model)

Functional co-ordination pattern selected under constraint

Task

Environmental

Organismic

Perception

Action

(Davids et al., 2008)

Coherent framework for understanding how co-ordination patterns emerge during goal directed behaviour

Participant and performance

• A former member of the men’s national gymnastics squad performed one trial of 12 continuous backward longswings on the Men’s Horizontal Bar at self-selected speeds in the following order: 3 normal, 3 fast, 3 slow, 3 fast

• He then completed a second trial performing a Kovacs. All trials were performed on a standard competition high bar.

Data Processing

• Motion data into Visual3D

• Butterworth filter with cut-off at 10Hz

• Calculated planar angles at shoulder and hip

wrist

shoulder

hip

knee

Mean RMSD values between Kovacs Prep & Action and Longswings performed at different self-selected speeds

Normal Fast 1 Slow Fast 2 Kovacs Prep 5 5 5 6 θS (°) Kovacs Action 6 6 7 5 Kovacs Prep 46 47 56 47

ωS (°s-1) Kovacs Action 61 56 62 51 Kovacs Prep 7 7 7 5

θH (°) Kovacs Action 22 19 23 18 Kovacs Prep 70 54 73 41

ωH (°s-1) Kovacs Action 183 156 183 151

Kovacs Prep = initial longswing

Kovacs Action = longswing before Kovacs

Kovacs and variations in longswings• The lower RMSD values for the fast longswings

indicates that varying the speed of the longswing can lead to greater similarities between the longswing action and the Kovacs skill.

• Functional variability of the longswing action may therefore be useful in the acquisition of the Kovacs, suggesting that longswing progressions should encourage the development of variable longswing movements.

• Interestingly, there were greater similarities in the hip joint motion observed in the fast longswings performed after a series of slower longswings, suggesting that sequence of speed variation may be important. Low and Cooke (2008)

Analysis of Results on Kovacs & longswings

• Sequential variation in the speed of longswings induced movements that have a greater similarity to those movements associated with a high level skill.

• Functional variability in the longswing action may therefore be beneficial to gymnasts in terms of acquisition of high level skills, such as the Kovacs. Low and Cooke (2008)

Conclusion• Variability can be positive and negative in sports-

specific tasks• Variation can assist in providing flexible movement

solutions for successful performance • Constraints can limit performance • Understanding the different dimensions of inter

and intra variability in technique, style and how they do or don’t explain performance in sport is key to not only biomechanists, but also performers, coaches, and teachers.

CASE STUDIES

Gary Sanderson: the biomechanics of a Sprinter

Gary is an 18 year old sprinterthe only difference is that he has Cerebral Palsy and wants to run at the next Olympics

The Problem: Gary was fitted with an ankle foot orthosis (or splint) to help support the ankle.But Gary’s foot was regularly collapsing as the foot was loaded during running causing great strain around the foot and ankle.

Copyright of Professor Jim Richards, University of Central Lancashire

Motion analysis showed the degree to which the ankle was collapsing

Copyright of Professor Jim Richards, University of Central Lancashire

Re-think

• Based on the information a redesign of the ankle foot orthosis (or splint) was conducted.

• The focus of this change was to provide greater stability about ankle joint.

• This in turn should help performance !?!

Copyright of Professor Jim Richards, University of Central Lancashire

The new orthosis shows no collapsing although the foot is still internally rotated

Before After

Copyright of Professor Jim Richards, University of Central Lancashire

Do we get an improvement of performance about the ankle?

• The ankle is more stable

• This should allow a better platform from which to push off

• This should lead to a significant increase in the power production

Copyright of Professor Jim Richards, University of Central Lancashire

Do we get an improvement of performance about the ankle?

Shortly after the fitting of the new orthosis Gary recorded his fastest ever time for the 100 m, 13.8 seconds, 1.5 seconds off his previous best time!

Copyright of Professor Jim Richards, University of Central Lancashire

Entertainment Applications

• Films• Television• Computer and video

games

Animation

                                                       

Facial Caption

Movie/Television• Seamless and believable

visual effects• Films

– “Titanic“– "Gladiator“– "The Mummy Returns", – "Star Wars Episode 1 - the

Phantom Menace”• Crowd Scenes• Stunt Work• Photorealistic foreground

characters