Cum arata un studiu al miscariilor in detectia minciunii

To freeze or not to freeze

 

A motion-capture approach to detecting deceit

 

Sophie Van Der Zee – Computer Laboratory, University of Cambridge, Cambridge, UK ;

Ronald Poppe – Information and Computing Sciences, Utrecht University,

Utrecht, The Netherlands ;

Paul J. Taylor Psychology, Lancaster University, Lancaster, UK ;

Psychology, University of Twente, Enschede, The Netherlands ;

Ross Anderson – Computer Laboratory, University of Cambridge, Cambridge, UK .

 

Address correspondence to: sophie.van-der-zee@cl.cam.ac.uk

 

Abstract

          We present a new robust signal for detecting deception:

full body motion.

Previous work on detecting deception from body movement has relied either on human judges or on specific gestures (such as fidgeting or gaze aversion) that are coded or rated by humans.

The results are characterized by inconsistent and often contradictory findings, with small-stakes lies under lab conditions detected at rates only slightly better than guessing.

Building on previous work that uses automatic analysis of facial videos and rhythmic body movements to diagnose stress, we set out to see whether a full body motion capture suit, which records the position, velocity and orientation of 23 points in the subject’s body, could yield a better signal of deception.

Interviewees of South Asian (n = 60) or White British culture (n = 30) were required to either tell the truth or lie about two experienced tasks while being interviewed by somebody from their own (n = 60) or different culture (n = 30).

We discovered that full body motion – the sum of joint displacements – was indicative of lying approximately 75% of the time.

Furthermore, movement was guilt-related, and occurred independently of anxiety, cognitive load and cultural background.

Further analyses indicate that including individual limb data in our full body motion measurements, in combination with appropriate questioning strategies, can increase its discriminatory power to around 82%.

This culture-sensitive study provides an objective and inclusive view on how people actually behave when lying.

It appears that full body motion can be a robust nonverbal indicator of deceit, and suggests that lying does not cause people to freeze.

However, should full body motion capture become a routine investigative technique, liars might freeze in order not to give themselves away;

but this in itself should be a telltale.

 

Keywords

deception;

movement;

nonverbal cues;

interview;

motion-capture;

automatic analysis

 

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A motion-capture approach to detecting deceit

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