Gait Recognition Examined

By Zach Segal, Published Sep 14, 2020, 10:14am EDT (Info+)

Facial recognition faces increasing ethical and political criticisms while masks undermine its effectiveness. One alternative is gait recognition but how realistic is using gait?

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IPVM investigates gait recognition's pros and cons compared to face recognition including interviews with a leading gait expert Professor Mark Nixon and a review of various research papers on the topic, explaining:

  • Gait Recognition Fundamentals
  • Accuracy vs Facial Recognition
  • Factors that Affect Gait Accuracy
  • Benefits of Gait
  • Gait Computationally Intensive
  • Enrollment Hard, Data Lacking
  • Appearance Vs. Model
  • 3D Images and Angle Simulation
  • China Watrix, Only Surveillance Gait Seller
  • Dahua Claims Record Accuracy
  • Gait Recognition Use in Court
  • Gait for Authentication/Access Control
  • Other uses for Gait

Executive *******

**** *********** **** * ******'* ****** body *** ********* ** ******** **** but ** ** ** ** **** limited *** ***** ** ** **** to ********* *** ****** ** ** or **** **.

******* *** ** ** *** ** accurate ** **** *********** *** ***** supplement **** *********** *** ***** ********** because ** *** ********* **********. **** also *** ** *** ** **** with * ***** *** **** **** recognition, ***** ** ****** **** *****, and ** **** ** *****. ***,** ***** **** *** ******* ******* gait *********** (*****'*******) ****** *** ******* ** **** *********** reflecting *** ********** ********* ***** ********, significantly ****** ********* *****, ****** ******* issues, *** ********* **** **********.

What ** **** ***********

**** *********** **** *******'* ******* ******* ** ******** ** ************ them **** *** ******** ****** ***** (left *** ***** *****, ~* ****** of *******) **** ********* ******** ***** PPF ************ **** ***** **********. ****, though, ** * ******** ***** **** technology ****** ** **** **** *** someone ***** (*.*., ***** '****'). *** ***** ** **** ****, ***********, posture, *** **** *** ******** **** alongside **** ********* *** ******* ***** factors.******* *** **** ************** ** **** **** ***** *** than **** *********** ******* **** *********** relies ** ****** ********.

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High ***** **** ********

****** **** ***********, **** *********** ******** a ******** ** ******. ************* *****, *** ********** **** ***********, **** IPVM **** ************ **** *****/****** ** ******* * second **** ****** *** ******* ** higher ******** *** **** ****** **********. This ***** **** *********** ** *** more *************** ********* **** ***** ********** because ** *** **** ****** ****** of ****** ****** ** ********** **.*** ***** ******* ****** **** *** *** *** achieved ** ******** ** **% **** 50 ******, **% **** **, *** 99% **** ** *** ********* *** test **** *** *** *** ********* so *** ******** *** *** ********** of *******. **** **** ********* **** gait ****** ******** **** **** ****:

******** *** ****** ** *** **** cycle ** ***** * *, **30 − ** ******, **** ***** ********* **** ***** ** ** ************ for good individual recognition. Increasing the number of consecutive frames for classification improved the results. The expanded time of analysis was required because body ***** ******* *** ******* *** *** ********* *** **** **** and, correspondingly, using long sequences makes recognition more stable to small inter-step changes in walking style.

***** **** **** "**** ***** ******* to ** ******" **** ************ ********* reaching **,*** ****** ******* **********.

Gait **** ******** **** **** ***********

**** *********** ** ***** ******** ** **** ***********. **** recognition ******** *****************%-**% ****** ********* ***** ****.**+% *** *** *** **** ********************* ** **** ******* *** ***** results *** ** ********** ******* **** are ***** ** ********** *********.

** ********,* ********** ** ***** ************ * **** ********* **** ********* an ******** ** **** **-**%. * key ********** ** **** *** ******* were ****** ** **.***/** ******* ** chest *****, ** **** *** ** most **** *****, *** ******* ***** shows *** ***** ******** *****:

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**** ******* * **,*** ****** **** set *** **** *** ****** ** 25 ***, ~** ******, ** ****** 2-D **** *** ******** ****** ****** to ******** ****-**** ***** *** ***** of ******* **** *** ****** ***** up. **** ****** * ****** **********-***** models (**** **** **** ** **********-*****) and ***** * *** ***** ********** had ********** ** **-**% *** * other ********** ******* * *** **%. Even ** *** ***** ********** ********* was ******* *** ******** ******** **%, the **** ********** ***** **** **** than **% ******** ** *** **** realistic ****.

Factors ********* ********: ****** *****, ********, *****, ******* ******

********, *****, ******* *******, *** **** importantly ****** ***** ****** **** *********** accuracy. ****** ***** ******* *********** ******* people **** ********* **** ********* *****.*** **** ** *************** ****** ***** ** *** **** difficult *** ********* ****** ********* **** recognition:

****** *****, *******, *** ********** *** most *********** ******— ***** *** ****** the **** ******** ** * ****** manner

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****** **** ************* ********* *****, **** ***** ** their *****, ***** *******, *** ***** carrying *******, ** **** ******* *** accuracy ** **** ***********.**** *********** *** ** ********** ******** *** ******** ******** *******. Clothes *** ******* ****** * ********** and *** **** ****** * ******’* walk.

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~20 *** ********

**** *********** *** **** **** **** 100 ***** **** ****** ** in **** *****. ***************** ******* **** ****** ***** **** *** ***** ****** people, ** ** *** *** ******* who ** * **** **** *** 16.7 *** *** ******* *** ** 6 **** ****:

*** ****** ** ****** ** * reasonable ******** ********** *** **** ***********. With ****** **********, *** **** ***** observe ****** ***********.

**** ***** **** * ~**-**** *** for * ***** ******. ** **** stated **** ** **-** ****** ** height, **** *********** ******* **** ***********. This **~*/*** ** **** **** ****** ******** *** **** ********* **** recognition.

Gait *********** **** ** ***** *****

**** ************* *** ******** ** ******* *** type ** **** ***** ** **** not ****** ** ***'* ****, ***** is ** ********* ******** ** ****** recognition.

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***** ******** ** ***** ** ****** gait *********** **** ** ***** ** a ****, ******** * ********, ***. will **** **** ****** *** *** much ******* ** *** *********/ ************** of *** **** ***********.********* ***** ******** ******** ** ******** gait *** **** ********* ********* ******* of *** **** ***** ** ******** gait *********** ****:

**** ** * *********** ** **** shape *** ********. ** *** *** rocks ** **** *****, ** ***** have ** *** *** **** ************ only, ** ******* **** ******** ***** change.

Gait *********** *********, **** ******** ******

**** *********** ** **** **** *************** intensive **** ************ ******* ** ******** multiple ******.**** *********** ** **** *************** **** face *********** ******* ** ****** ** sequences ** ****** ******* ** * single **** *****. ********* ***** **** APNews **** *********** ******** **** ******** computers **** ***** **********:

**’* **** ******* **** ***** **********, computationally, ... ** ***** ****** ********* to ** **** ******* *** **** a ******** ** ****** ****** **** a ****** *****.

**** ***** **** **** *********** **** more ********* **** ************. *** ********** grows ************* **** ******** ****** *** combined *** **** *********** ******** ~* full ****** ** ******. *** ******** number ** **** **** **** *** 25.

Gait ********** ****, **** *******

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*******, ********** ** *** **** *** datasets *** ********** *****.** *************** * ******* ******* *** ******* are ******** **** ******** ******* *** used ** ******* ********* ****** (******* to *** *****). **** ** **** time, *****, *** ********-********* **** ********* a ****** ****-******* **** *****.

**** *********** **** ** **** **** accessible ******* *********** **** ****** ** their ***********' **** ******, ******’* ********, passports, ****** ****. *** ** *** United ******,** ** ***** ** ********* ** *** ******** ** ****** on ****** ***** *** *** ********.*** ******* **** *******,**-*****, ******** **,*** ******'* **********'* **** 14 ****** *** ******* ** ** for ******** ******** ****. ** ** also ********** **** ******* ** *****, which ***** ******* ****** ****** *** it.**** **** ** **** ***** **** companies **** ***** **** ** ******* algorithms, ***** *** ********** ** **********, and **** ********** **** ****** *** more ******. **-*****'* *******'* ***** *** accuracy ** *** **** ******** **** of ********* **** ****** ** **** ~35% **** ******* ** *** ****** to ~**% **** **,***. ** *** trend *********, ** ***** ****** ~**% accuracy **** * ***,*** ****** *******

Appearance **. *****-*****

***** *** *** **** ******* ** algorithms, **********, *** *****-*****. **********-***** ****** turn ******* **** * ********** *** use **** *** ********. **********-***** *** the **** ****** ******* **** *** simple, ****, *** **** *************** *********.**** ******* **********-*********** ******* ******** ****** **** *** GEI, **** ****** *****, ***** ****** are ********* **** *********** *** ***** silhouettes *** ******** ******** ******** ******* shades ** **** ***** ******** ******.

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*****-***** ********** *** ****** ** *** human **** *** ***** ** * person ** ****** * ***** **** represents **** ******* ** * **********. They *** **** *********** *** *************** intensive ******* **** ******* **** *****. They *** **** ********* ** ***** and ***** ********* ******* *** ****** they ****** *** **** ******** ** outside *********. * ******** ** **** can ****** * ********** ** ** appearance-based ********* *** * *****-***** ********* should ** **** ********. ******** *** camera ***** *** * ***** ****** on ***********,*** ****** ****** ** *** **** regardless ** *** ****** ** *** footage **** *** ***** ****.

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3D ******

***** **** **** **** *** **** resilient *** ******* ********** *** **. He **** ** ******** ******** ******* to ****** * ** ***** ** the ******. **** *** ** *********** because ** ******** **** *********** ***-***, to ****** *** *** ** ******** is ******* ** ******** *******, *** combining **** **** ******** ******* ** much **** *************** ********* **** ***** a ****** ******.**********- ** *****-*************** *** ** **.

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Simulating ******

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*** **** *** ************* **** ******** ** ******** **** other ****** ****** ***** **** ************ mitigates *** ****** ** ********* ****** angles ***** *** ********* ******** *******, which **** *** ** ***********:

***** ******* ******* * ***** ********** and *********** ******** ****** ************, ***** limits *** *********** ** **** ***** surveillance *********.

**** **** **** ** ***** *-* silhouettes **** ********* ****** **** * ~30 ********** ***** ***** ** ********, compared ** ***** ********** **** *** 60+ ********** ***** ***** **** ******** images ***** **** ********* ******.

One *** *******, ****** ** ******* **** ***********

******** * ******* ******** ****** ******* that*** ********* **** ************************ ** *** ****** ** *** People's ********** ***** *** ** **** ** the***** ************ **************. ** **** *** ***** ****** else ******* *** **********. ****** ****** their ******** ** **% ******** *** works ** ***/***** *** *** *** specify *** ** *** ************. ****** says **** ********* ** ********* ********* to *********** ******** *** **** *** require ********* ********.

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****** *** ***** ******** ****** **** *** *********’* **** **** analysis ***** ** ********* ** ********:

******** **** **** ***** ****** *** recognition ***** *** ** ******* *** of * ******’* ****

****** **** *** ************ ***** **** ** * ************ use **** *** ****-**** *** ************* by *** ******* ****** *** ********** for ** *****, ********** **** * TB ** ****** *******.** ******* ****** **** ** **** they**** ** ************ ** **** ~$** million ** ********** ** ********* ****** China.**** ***** ******** ******:

** *** ********* ******* **** ****** on ******** **************, **** ** ******** suspects **** * ******* *****, ... Currently, ***** *** ***** ***,*** ****** criminals ** *** ***** *** ********. [Our ********’*] ******** ******** ***** **** a ***** **** ******.

**** ********* ***** ***** ****** ******* more ** *** ********** *** *** use ** *** ***.

********,****** ********* ********* ********************/**** ******** ***** ** **** ******* tracing.

** ******** ** ***** ******* *** in *****, ** *****/* ** ** data, ****** **** *** ***** ******* outside ** ***** ** ******* ***** 2018. ***** *** *** ****** ***** for ****** *** **** ***********. ** would ****** ** *** **** ***** competition *** **** ****** ******* ****** if ****** *** **** ** ******* 96% ******** ** ****-***** *****.

Dahua ****** ** ***** ****** ** **** *********** ****; **** ****** ******

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** ****** ****,***** ********* **** ****** *** ****** ** the*****-* **** *********** *******.*** **** *********** ** ** ****** ** *** subjects ******* **** ******** ******. ** is *********** ******* ** *** ***** backgrounds, * **** ******** ** ***** angles, *** ** **** ** * low ****** (** ****-****). ****-***** ******** could ** **** ********* **** *****-* accuracy. *** ***** ****** **** **** makes ****** ***** ** ************* ****** ** ********* **** ***** very **** *** **** *** ****** in *** *******.** *** ***** ********,

**** **** ********* ... ******* *** person *** ***** ******* *** ************ between *******. **** ** ** ****** a ***** ********, ** ** **** life ****** ***** **** ******** **** their ****** ************; ************, **** ********* allows *** *** ******** ** * model *** ******** ** *** ******* of **** *********** *** ** ************* solved.

***** ********.*% ******** ** * ***** *******, 94% ** ******** **** ****, *** 87% ** ******** ** *****. ** have *** ***** *** ********** ** Dahua ******* **** ***********.

******:****** *** ********* **** ****** *****'* ****** ** the *****-*. **** ***** **.*% ******** on * ***** *******, **.*% ** subjects **** ****, *** **.*% ** subjects ** *****.

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Examples ** *** ** ****** ******* ** *****

**** *********** *** **** **** ** evidence ** ****** ** ***** *** Denmark

  • ***** ***** **** *** ******** ****** have**** **** *********** ***** **** *** famously ****** * ******* ** **** by **** *********** ¾ ****** *******. They *** ** *** **** ** times ******* ********* *** *** ****.
  • **** *********** *** **** ** ********* evidence ** * ******* ** ******* in ****. ******* ***** ****** *** crime *** ******** **** ******** ******* of *** ******* ** ******** *** was *** **** *** *** *************.

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American ******* ** ******** ******* ***** *******

** ******* ***** ******* ** ******** ********(*** ******** *********** ** *** ******** Academy ** ******** ********)***** ******* **** ***** **** ************* ******** ** ****.

*********, ****** ****** ***** **** ******** with *******, ** **** ****** *** other **** ** ******** *********** **** disciplines ******* ***** *********** ***** ** practice, ***** *****, *** ************ ************ in ******** *********.

Gait *********** *** ************/****** *******

********* *** **** *********** *** ** used *** ******* ****** *******/************ ******* a *******’***** *****,***** *******, *********. ****** **** ***********, **************, ** manual ************ **** ******* *** ** done *********/************* ******* ************.**** ** * *** **************** ** ******* *** ************* ** security ***** ****** ****** ** ***-*** of *********, **** ******, ** **** recognition *** ****** *** ***** ********. Users ***** **** **** * **** that ***** ************* *** ****. ** addition, ****** ***’* **** ** ***** about **** ***** ******** ***** *****, looking **** ** ***** ******, ** wearing ******* **** ******** * *** feature.

UnifyID *** **********-***** ************** ********

********* * ********** ******* **** ** focused ** ******** ************** ******* ********** including **** ***********. **** **** ******** mobile *****-***** **** ************************** ******* **** ** ********** **** access *******, **-***-*********, ******* ******, *** other ****.******* **** **** **** ******** ***** on ******** *** ******* **** **************, including *****-*** ****** ******* *********** ** face *********** ************. ******* **** **** that *** ********* ** ****** ** the ****'* ***** *** ****** ***** behavior. ** ***** ** ****** *** by ***** ****** ** * ********* pocket, ******* ********* *****, *** ***** factors **** ****** **** ***********, *** UnifyID **** *** ********* *** ***** that ***** ******* *** ***** ***. It ***** ** ****** ** ********* you **** ***** ********* *******, *** needs ** ***** *** **** **** change.

**** **** **** *** ********** ** c********* **** ************, *** ** **** not ****** **:

*** ******** **** ******** ** ** par **** ******** ************ ***********, **** a */**,*** ***** ******** ****.

Other ********** - ***** *****, ***** *******

*********** **** **** ******** ***** ***** sensors, ***** ***** ** *********, ******* of *******. **** ***** ******* ******** and **** **** *** ********** ********* preventing ******* ********.* **** ** **** *********** ***** ***** *****, ***** ***** be **** **** ***** *** **** cameras *** **** ** *** ******** scenario.

Gait ******** *** ********** ********, ******* *******, ******** ****

**** *** **** ** **** ** watch ****** *******, *** ********** ********, and **** ***** ********** *******.****** **** ***** *************** *********** ** **** ** **** people *** **** ****, **** ** elderly *********** *** **** ****** ****. Cameras ***** ** **** ** **** for ****** *** **** ****** *** then ** *** *** **. **** recognition ****** **************** ******* ***** **** *********** ****** **** ***** ******* ***** ** ****** **** ******** to ******* *** *****:

** *** ******, * **** **** to ***** *** ************ ** ***** health ** ****** **** *** **** they ****

** ***** **** ** **** ** look *** ********** ********.* **** **** ******* **** ********* a *********** ** ***** ***** **** *** analyze ********.**** **** *************** ***** *************** ** ** *** **** **** because **'* ***** ** ***** ***** and ** *********** *** *** **** reason. **** **** ** ****** ****** specific *********** *** *** **** ** someone ** ******** ************ *** ****** information ***** ***** ****, ** ** fast, ****, **********, ***. ***** **** principles ***** ** ******* ** ********* pedestrian ********. *** ***** *** **** areas **** **** ******* *** *****/**** pedestrians **** *** **** ** *********** or *****.** **** *** ** **** ********* *********** ** ******, ***, *** physical *************** ** *********** ***** ***** less ********, *** **** *************** *********** than **** ***********.

*******

**** *********** *** **** ** ********** where **** *********** *** ***** ********** don’t ** ** ***** **** ********** surveillance *******. ** *** **** **** access *******/************** * ****** *** **** private **** ********** **** ** ********* to **** *********. *******, *** **** of ********* ******* ** *** ******* gait *********** ** * **** *** technology *** ***** *****. ******* ***** stem **** **** ***********'* ***** ************* demand, ***** ********, *** ****** ** factors **** ** ***** ** ****, the ********** ** ********** ****, ** lack ** ********, ** ** * bad ****.

Comments (16)

****, ***** ****!

*******, ** *** **** *** *************** on ******* **** ** ******** ************ you ***** **** **** ** *******, please *** ** ****.

Agree
Disagree
Informative
Unhelpful
Funny

****, ****** **** ***. *** ******** of **** ******** ** ****** ** accuracy. *'* **** ** *** **** hold ******* ** ********* ***** *********** in * ********** *** ********** ***. When * ****** ***** *% ********, what **** **** ****? ** *** all ********** *** **** ***** ***** Positive *** ***** ******************* ******* ******** **** *** ************** mode. *'* ********* ** ****** ******* much ** **** * ****** **** about ***** *** **********, ********** **** it's ********* ** ********. *** *'** believe ****!

Agree
Disagree
Informative
Unhelpful
Funny

***** *** ****. *** * *****. Accuracy *** ************** ** **** *********** to ******** ******* ** ********* *** the ******* *** **** *********.

Agree
Disagree
Informative
Unhelpful
Funny

**** **** * *** ************ * face-rec ******* ** **********, (****-****), **** is *** ******** **** ******** *-****** agencies **** ********* ***.

Agree
Disagree
Informative: 2
Unhelpful
Funny

* ****** ** ** ***** ******* this -

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Agree: 1
Disagree
Informative: 2
Unhelpful
Funny: 9

***** ** **** *** ********** *** Monty ******Ministry ** ***** ***** before I did.

***, **** ********* ** **** * feasible ******** ** ***** **** *** being ******** ****'* ***** ** *** analytic. ********* **** *** *****, ** ** *** ** *** easiest ********* ** ****** ***** ** simply ********* *** *** ***** ********* walk ******.

Agree: 1
Disagree
Informative
Unhelpful
Funny

* ****** **** ******* ******** ****** classify **** *********** ******** ***** ** either ***** ** *****-**** ***** *******. Model-free ***** ***** ** *********** ******** of *** ******** ** ** *********** object **** *****'* ******* ** *** it ** * ***** *****. *** call ********** ***** ******** * ***-******** of *****-**** ***** *******. ** ** fair, ** ***** **** *** *** Gate ******/******* ** *** *** ********. To **, * **** ** ***** that **** ****** ******* **** *** seem **** **** * **** ** Silhouette **************. ** *** *** *****-**** falls **** ***** **********: ******* ****, Contour, *** **********, *** ***** *******.

Agree
Disagree
Informative
Unhelpful
Funny

***. **** ** **** ** ****** appearance-based **** ***********.

Agree
Disagree
Informative
Unhelpful
Funny

**'* * ***** **** *** ********** couldn't **** **. **** *** * great ******* **** **** **** *********** as *** ****** ** **************, *** it *** * *** ***** ** it's **** * *****.

Agree
Disagree
Informative
Unhelpful
Funny

*** ** ****** * ***** *******? Did ** ****** *** **** ***********? It *** * ***** ******* *** what *** *** ******* ** **** actually ***** **** ***********.

Agree
Disagree
Informative
Unhelpful
Funny

*** ******* ****'* *******, *** ** worked *** ****** ************ **** ***** (very, **** *********) ************ **********/************ **** followed. *** ***, **** *** **** gait *********** ***** **** ***** *******.

*** ******* **** *** ****'* *** performance ** *** *******, ** *** the ********* ************ **** *** *** it ** ****. **** ***** ** the **** ** ****** ********, ***** meant **** ** ****** ****'* **** the ************ **** *** ********, ** wouldn't ***** ******. *** **** *** right ********, ** *** ********** ********** with ** ********* ***** ****** ** failures.

* **** ***** **** **** **** a *** *** ***** ** ***** of *** ********** ***** ******** ** make *** ****** **** ** ****. It ****** ****** *** ** *** that *** ****** * ****** *** every * ****** ** *******. ** reality, **'* ****** ******* ** **** of *** ********* ********* ***** ****, but ~* ***** ***, **** ****'* nearly ** ******.

Agree
Disagree
Informative: 1
Unhelpful
Funny

**** ********!

****, **** *********) ************ **********/************...***** ** *** ********** ***** ********

**'* **** ** *** ******** **** those ***********. **'* ********* **** **** and * **** ********** ***** **** topic, *** ********** ***** ********** **** but ** **'* *** ******* ** costly ** *** ** **********, ******** will ******.

Agree
Disagree
Informative
Unhelpful
Funny

**** *********** *******.

******** * ***’* *** **** ** a ******* ***** ** ***********, ** seems ****** *** ****-***** ********* ** described ******* *** *** ** *** article.

**** *** ****!

Agree
Disagree
Informative
Unhelpful
Funny

***** ***, ******. *** **** ***** to ** *** *** ********** ** being ****.

Agree
Disagree
Informative
Unhelpful
Funny

******:****** *** ********* **** ****** *****'* ****** ** the *****-*. **** ***** **.*% ******** on * ***** *******, **.*% ** subjects **** ****, *** **.*% ** subjects ** *****. * **** ***** this *********** ** *** *******.

Agree
Disagree
Informative
Unhelpful
Funny

******: ***************** ******* **** **** **** *********** ******** at ***** ** ***** ** ****** and **** ** **** *** ***** high ****** *** *** ********. **** would **** * ~**-**** *** *** a ***** ******.

Agree
Disagree
Informative
Unhelpful
Funny
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