Person Identification from Drones by Humans: Insights from Cognitive Psychology

The deployment of unmanned aerial vehicles (i.e., drones) in military and police operations implies that drones can provide footage that is of sufficient quality to enable the recognition of strategic targets, criminal suspects, and missing persons. On the contrary, evidence from Cognitive Psychology suggests that such identity judgements by humans are already difficult under ideal conditions, and are even more challenging with drone surveillance footage. In this review, we outline the psychological literature on person identification for readers who are interested in the real-world application of drones. We specifically focus on factors that are likely to affect identification performance from drone-recorded footage, such as image quality, and additional person-related information from the body and gait. Based on this work, we suggest that person identification from drones is likely to be very challenging indeed, and that performance in laboratory settings is still very likely to underestimate the difficulty of this task in real-world settings.

[1]  V. Bruce,et al.  Face Recognition in Poor-Quality Video: Evidence From Security Surveillance , 1999 .

[2]  Tim Valentine,et al.  CCTV on trial: Matching video images with the defendant in the dock , 2009 .

[3]  Vicki Bruce,et al.  Evaluating the effectiveness of pixelation and blurring on masking the identity of familiar faces , 2001 .

[4]  Ahmed M. Megreya,et al.  Unfamiliar faces are not faces: Evidence from a matching task , 2006, Memory & cognition.

[5]  V. Bruce,et al.  Matching identities of familiar and unfamiliar faces caught on CCTV images. , 2001, Journal of experimental psychology. Applied.

[6]  M. Bindemann,et al.  Exploring the time course of face matching: Temporal constraints impair unfamiliar face identification under temporally unconstrained viewing , 2011, Vision Research.

[7]  Matthew C Fysh,et al.  Individual differences in the detection, matching and memory of faces , 2018, Cognitive research: principles and implications.

[8]  Vicki Bruce,et al.  Matching the faces of robbers captured on video , 2001 .

[9]  Alice J. O'Toole,et al.  FRVT 2006 and ICE 2006 Large-Scale Experimental Results , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Andrew Russ,et al.  Individual differences in face identification postdict eyewitness accuracy , 2012 .

[11]  Matthew C Fysh,et al.  Person identification from aerial footage by a remote-controlled drone , 2017, Scientific Reports.

[12]  Matthew C Fysh,et al.  Effects of time pressure and time passage on face-matching accuracy , 2017, Royal Society Open Science.

[13]  Markus Bindemann,et al.  Me, Myself, and I: Different Recognition Rates for Three Photo-IDs of the Same Person , 2011, Perception.

[14]  Anastasios Tefas,et al.  Discriminatively Trained Autoencoders for Fast and Accurate Face Recognition , 2017, EANN.

[15]  Shaogang Gong,et al.  Investigating Open-World Person Re-identification Using a Drone , 2014, ECCV Workshops.

[16]  A. Young,et al.  Recognizing Faces , 2017 .

[17]  Michael G. Reynolds,et al.  Unfamiliar Face Matching With Frontal and Profile Views , 2018, Perception.

[18]  Rob Jenkins,et al.  Face Recognition by Metropolitan Police Super-Recognisers , 2016, PloS one.

[19]  A. Young,et al.  Understanding face recognition. , 1986, British journal of psychology.

[20]  K. Nakayama,et al.  Super-recognizers: People with extraordinary face recognition ability , 2009, Psychonomic bulletin & review.

[21]  Josh P. Davis,et al.  Identification from CCTV: Assessing police super‐recogniser ability to spot faces in a crowd and susceptibility to change blindness , 2018 .

[22]  Andrew Zisserman,et al.  Deep Face Recognition , 2015, BMVC.

[23]  Markus Bindemann,et al.  Human–Computer Interaction in Face Matching , 2018, Cogn. Sci..

[24]  Markus Bindemann,et al.  Forensic face matching : A review , 2017 .

[25]  Robert A. Johnston,et al.  The Effect of Image Pixelation on Unfamiliar‐Face Matching , 2013 .

[26]  Rob Jenkins,et al.  Camera-to-subject distance affects face configuration and perceived identity , 2017, Cognition.

[27]  G. Pike,et al.  When Seeing should not be Believing: Photographs, Credit Cards and Fraud , 1997 .

[28]  Markus Bindemann,et al.  Generalization across view in face memory and face matching , 2014, i-Perception.

[29]  Carina A. Hahn,et al.  Dissecting the time course of person recognition in natural viewing environments. , 2016, British journal of psychology.

[30]  M. Bindemann,et al.  Matching Faces Against the Clock , 2016, i-Perception.

[31]  Vaidehi S. Natu,et al.  Unaware Person Recognition From the Body When Face Identification Fails , 2013, Psychological science.

[32]  Sarah Bate,et al.  Solving the Border Control Problem: Evidence of Enhanced Face Matching in Individuals with Extraordinary Face Recognition Skills , 2016, PloS one.

[33]  Tim Rakow,et al.  Who can recognize unfamiliar faces? Individual differences and observer consistency in person identification. , 2012, Journal of experimental psychology. Applied.

[34]  Andrew J. Edmonds,et al.  Familiar and unfamiliar face recognition: A review , 2009, Memory.

[35]  Ahmed M Megreya,et al.  Matching faces to photographs: poor performance in eyewitness memory (without the memory). , 2008, Journal of experimental psychology. Applied.

[36]  David White,et al.  Error Rates in Users of Automatic Face Recognition Software , 2015, PloS one.

[37]  Ahmed M. Megreya,et al.  Matching Face Images Taken on the Same Day or Months Apart: the Limitations of Photo ID , 2013 .

[38]  Julianne H. Ayyad,et al.  Recognizing people from dynamic and static faces and bodies: Dissecting identity with a fusion approach , 2010, Vision Research.

[39]  A. O'Toole,et al.  The Role of the Face and Body in Unfamiliar Person Identification , 2013 .

[40]  J. Gibson.  The visual perception of objective motion and subjective movement. , 1994, Psychological review.

[41]  Claus-Christian Carbon,et al.  An Easy Game for Frauds? Effects of Professional Experience and Time Pressure on Passport-Matching Performance , 2017, Journal of experimental psychology. Applied.

[42]  Josh P. Davis,et al.  Investigating predictors of superior face recognition ability in police super-recognisers , 2016 .

[43]  L. T. Troland.  Helmholtz's Treatise on Physiological Optics , 1926 .

[44]  A. Burton,et al.  Passport Officers’ Errors in Face Matching , 2014, PloS one.

[45]  Paul Miller,et al.  Verification of face identities from images captured on video. , 1999 .

[46]  A. Burton,et al.  The Glasgow Face Matching Test , 2010, Behavior research methods.

[47]  Markus Bindemann,et al.  Finding needles in haystacks: identity mismatch frequency and facial identity verification. , 2010, Journal of experimental psychology. Applied.

[48]  A. Burton,et al.  Variability in photos of the same face , 2011, Cognition.

[49]  Megan H. Papesh,et al.  Photo ID verification remains challenging despite years of practice , 2018, Cognitive Research: Principles and Implications.

[50]  Alice J. O'Toole,et al.  Face Recognition Algorithms Surpass Humans Matching Faces Over Changes in Illumination , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[51]  Robert A. Johnston,et al.  Special Issue on Forensic Face Matching , 2013 .

[52]  Matthew Q. Hill,et al.  Perceptual expertise in forensic facial image comparison , 2015, Proceedings of the Royal Society B: Biological Sciences.

[53]  Rob Jenkins,et al.  Face detection dissociates from face identification , 2017 .

[54]  Ramakant Nevatia,et al.  SPOT Poachers in Action: Augmenting Conservation Drones With Automatic Detection in Near Real Time , 2018, AAAI.

[55]  Rob Jenkins,et al.  Identifiable Images of Bystanders Extracted from Corneal Reflections , 2013, PloS one.

[56]  V. Bruce,et al.  Effects of lighting on the perception of facial surfaces. , 1996, Journal of experimental psychology. Human perception and performance.

[57]  Swami Sankaranarayanan,et al.  Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms , 2018, Proceedings of the National Academy of Sciences.

[58]  J. Gibson.  The visual perception of objective motion and subjective movement. 1954. , 1994, Psychological review.