Personal Information in Searching for Faces

Participants searched for a target on a television monitor either after they viewed pictures and received physical information about the target or received that information augmented by personal information. Based on a levels of processing perspective we predicted that the addition of personal information would stimulate deeper processing and result in better identification performance. Personal information did increase identification accuracy, as anticipated. Personal information also increased the duration of time spent on the search task relative to a distractor task, suggesting that personal information may have done more than deepen the processing at the time of encoding. In the current climate of terrorism, this increase in identification performance via a surveillance camera has clear applied significance.

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Eyewitness identification performance is not affected by time-of-day optimality

Scientific Reports ◽

10.1038/s41598-021-82628-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sergii Yaremenko ◽

Melanie Sauerland ◽

Lorraine Hope

Keyword(s):

Eyewitness Identification ◽

Time Of Day ◽

Decision Time ◽

Identification Accuracy ◽

Optimal Time ◽

Identification Performance ◽

Accurate Identification ◽

Facial Stimuli ◽

Time Accuracy ◽

Accuracy Relationship

AbstractThe circadian rhythm regulates arousal levels throughout the day and determines optimal periods for engaging in mental activities. Individuals differ in the time of day at which they reach their peak: Morning-type individuals are at their best in the morning and evening types perform better in the evening. Performance in recall and recognition of non-facial stimuli is generally superior at an individual’s circadian peak. In two studies (Ns = 103 and 324), we tested the effect of time-of-testing optimality on eyewitness identification performance. Morning- and evening-type participants viewed stimulus films depicting staged crimes and made identification decisions from target-present and target-absent lineups either at their optimal or non-optimal time-of-day. We expected that participants would make more accurate identification decisions and that the confidence-accuracy and decision time-accuracy relationships would be stronger at optimal compared to non-optimal time of day. In Experiment 1, identification accuracy was unexpectedly superior at non-optimal compared to optimal time of day in target-present lineups. In Experiment 2, identification accuracy did not differ between the optimal and non-optimal time of day. Contrary to our expectations, confidence-accuracy relationship was generally stronger at non-optimal compared to optimal time of day. In line with our predictions, non-optimal testing eliminated decision-time-accuracy relationship in Experiment 1.

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The effect of a secondary task on identification accuracy of oxygen saturation ranges using an enhanced pulse oximetry sonification

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931213601143 ◽

2016 ◽

Vol 60 (1) ◽

pp. 628-632

Author(s):

Estrella Paterson ◽

Penelope Sanderson ◽

Neil Paterson ◽

David Liu ◽

Robert Loeb

Keyword(s):

Oxygen Saturation ◽

Secondary Task ◽

Ambient Noise ◽

Visual Display ◽

Identification Accuracy ◽

Future Research ◽

Identification Performance ◽

Arithmetic Task ◽

Disruption Effect ◽

The Difference

In the operating theatre, anesthesiologists monitor an anesthetized patient’s oxygen saturation (SpO2) with a visual display but also with an auditory tone, or sonification. However, if the anesthesiologist must divide their attention across tasks, they may be less effective at recognising their patient’s SpO2 level. Previous research indicates that a sonification enhanced with additional sound dimensions of tremolo and brightness more effectively supports participants’ identification of SpO2 ranges than a conventional sonification does. This laboratory study explored the effect of a secondary task on participants’ ability to identify SpO2 range when using a conventional sonification (LogLinear sonification) versus an enhanced sonification (Stepped Effects sonification). Nineteen non-clinician participants who used the Stepped Effects sonification were significantly more effective at identifying SpO2 range ( Md = 100%) than were 18 participants using the LogLinear sonification ( Md = 80%). Range identification performance of participants using the Stepped Effects sonification tended to be less disrupted by a concurrent arithmetic task (drop from Md = 100% to 95%) than it was for participants using the LogLinear sonification (drop from Md = 80% to 73%). However, the disruption effect in each case was small, and the difference in disruption across sonifications was not statistically significant. Future research will test the sonifications under more intense cognitive load and in the presence of ambient noise.

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The Effect of Pre-Event Instructions on Eyewitness Identification Stage 1 Registered Report Manuscript

10.31219/osf.io/sk5bc ◽

2021 ◽

Author(s):

Mario J. Baldassari ◽

Kara N. Moore ◽

Ira Hyman ◽

LORRAINE HOPE ◽

Eric Mah ◽

...

Keyword(s):

Systematic Review ◽

Exposure Duration ◽

Eyewitness Identification ◽

Identification Accuracy ◽

Identification Performance ◽

Identification Stage ◽

Lineup Identification ◽

Stage 1 ◽

Future Work

Research on eyewitness identification often involves exposing participants to a simulated crime and later testing memory using a lineup. We conducted a systematic review showing that pre-event instructions, instructions given before event exposure, are rarely reported and those that are reported vary in the extent to which they warn participants about the nature of event or tasks. At odds with the experience of actual witnesses, some studies use pre-event instructions explicitly warning participants of the upcoming crime and lineup task. Both the basic and applied literature provide reason to believe that pre-event instructions may impact eyewitness identification performance. In Experiment 1, we will test the effect of pre-event instructions on lineup identification decisions and confidence. Participants will receive non-specific pre-event instructions (i.e., “watch this video”) or eyewitness pre-event instructions (i.e., “watch this crime video, you’ll complete a line-up later”) and complete a culprit absent or present lineup. In Experiment 2, we will manipulate exposure duration and pre-event instructions to determine if pre-event instructions differentially impact high or low quality eyewitness events. If pre-event instructions impact eyewitness identification accuracy, then the findings of existing studies need to be considered in the context of their pre-event instructions and future work will be needed to determine how instructions interact with existing systems and estimator variables.

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Radar Emitter Individual Identification Based on Convolutional Neural Network Learning

Mathematical Problems in Engineering ◽

10.1155/2021/5341940 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Wei Sun ◽

Lihua Wang ◽

Songlin Sun

Keyword(s):

Identification Accuracy ◽

Individual Identification ◽

Identification Performance ◽

Neural Network Learning ◽

Hilbert Huang Transform ◽

Network Learning ◽

Radar Systems ◽

Mode Decomposition ◽

Signal Image ◽

Real Time Identification

Radar Emitter Individual Identification is a key technology in modern electronic radar systems. This paper will focus on Radar Emitter Individual Identification (REII). Based on the advantages of Empirical Mode Decomposition (EMD) and bispectrum in signal processing, we propose an REII method based on the CNN. Firstly, the radar emitter signal is preprocessed. Secondly, the Hilbert–Huang Transform (HHT) spectrum and bispectrum are combined to form an image of the signal. Finally, in order to avoid loss of information and achieve the potential identification performance improvement, the signal image obtained is identified by the optimized CNN. Experimental results based on the measured signals show that the proposed method has high identification accuracy and is capable of meeting real-time identification requirements. The deep-learning-based identification method proposed in this paper has strong generalization ability and adaptability, which provides a new way for REII.

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Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications

npj Flexible Electronics ◽

10.1038/s41528-020-00092-7 ◽

2020 ◽

Vol 4 (1) ◽

Cited By ~ 3

Author(s):

Zixuan Zhang ◽

Tianyiyi He ◽

Minglu Zhu ◽

Zhongda Sun ◽

Qiongfeng Shi ◽

...

Keyword(s):

Deep Learning ◽

Gait Analysis ◽

Personal Information ◽

Low Cost ◽

Wearable Sensors ◽

Sensory Information ◽

Virtual Space ◽

Identification Accuracy ◽

Wearable Electronics ◽

Analysis Methods

Abstract The era of artificial intelligence and internet of things is rapidly developed by recent advances in wearable electronics. Gait reveals sensory information in daily life containing personal information, regarding identification and healthcare. Current wearable electronics of gait analysis are mainly limited by high fabrication cost, operation energy consumption, or inferior analysis methods, which barely involve machine learning or implement nonoptimal models that require massive datasets for training. Herein, we developed low-cost triboelectric intelligent socks for harvesting waste energy from low-frequency body motions to transmit wireless sensory data. The sock equipped with self-powered functionality also can be used as wearable sensors to deliver information, regarding the identity, health status, and activity of the users. To further address the issue of ineffective analysis methods, an optimized deep learning model with an end-to-end structure on the socks signals for the gait analysis is proposed, which produces a 93.54% identification accuracy of 13 participants and detects five different human activities with 96.67% accuracy. Toward practical application, we map the physical signals collected through the socks in the virtual space to establish a digital human system for sports monitoring, healthcare, identification, and future smart home applications.

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Does Accountability and an Automation Decision Aid’s Reliability Affect Human Performance in a Visual Search Task?

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931213601530 ◽

2017 ◽

Vol 61 (1) ◽

pp. 183-187 ◽

Cited By ~ 3

Author(s):

Smruti J. Shah ◽

James P. Bliss

Keyword(s):

Visual Search ◽

Undergraduate Students ◽

Human Performance ◽

Search Task ◽

Visual Search Task ◽

Identification Performance ◽

Identification Task ◽

Increasing Operator ◽

Performance Errors ◽

Incorrect Information

Some automation aids are not 100% reliable and can therefore provide incorrect information to users. If humans trust and comply with faulty automation aids, performance errors may result. In combat identification, performance errors may include fratricide or failure to identify enemies. In operator-automation teams, human accountability may reduce errors resulting from over-compliance and automation bias. The goal of the proposed study was to evaluate if reliability of an automation aid (60%, 80%) and accountability level (accountability, non-accountability) would influence human performance on a visual search task. Fifty-two undergraduate students performed a simulated combat identification task, aided by automation. Those in the 60% reliability condition committed more identification errors. However, this difference was eliminated for accountable participants. The findings suggest increasing operator accountability may improve identification performance and meliorate the adverse effects of unreliable automation.

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Research on Oil Painting Image Extraction and Identification Method based on Intelligent Vision

CONVERTER ◽

10.17762/converter.254 ◽

2021 ◽

pp. 742-749

Author(s):

Xianjun Yu

Keyword(s):

High Efficiency ◽

Visual Detection ◽

Feature Fusion ◽

Identification Accuracy ◽

Identification Performance ◽

Oil Painting ◽

Oil Paintings ◽

Detection Model ◽

Identification Method ◽

Feature Difference

A high-precision and high-efficiency oil painting identification method is the auxiliary basis for authenticating works, because it can improve the efficiency and credibility of oil painting identification. Therefore, an oil painting image extraction method based on intelligent vision was proposed.An intelligent visual detection model was constructed to obtain the characteristics of oil painting images.The oil painting feature fusion method based on intelligent vision was adopted to integrate the color and shape features of oil painting features, calculate oil painting feature difference coefficient and difference feature threshold, and realize oil painting image extraction by oil painting image extraction rules.The research results verified that the proposed method could effectively identify the authenticity of oil paintings. Compared with the expert identification method and the identification method based on deep learning, it can be seen that the method had the highest identification accuracy, the shortest identification time, the best anti-interference, and the remarkable identification performance, so it had a high application value.

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Metamemory and Lineup Instructions: Asking Eyewitnesses to Recollect Reduces False Identification

10.20944/preprints201812.0012.v1 ◽

2018 ◽

Author(s):

Nicola Guerin ◽

Nathan Weber ◽

Ruth Horry

Keyword(s):

Good Predictor ◽

Process Model ◽

Eyewitness Identification ◽

Dual Process ◽

Identification Accuracy ◽

False Identification ◽

Identification Performance ◽

Decision Confidence ◽

Delayed Choice ◽

Simultaneous Elimination

Little theoretically-informed research investigates how non-standard eyewitness identification tasks or metacognitive instructions might improve identification accuracy. We used a continuous dual-process model of recognition to explain familiarity-based identification errors and design modified lineup tasks and metacognitive instructions that increased eyewitness recollection and discriminability. In four studies we examined identification performance across lineups (standard simultaneous, elimination, delayed-choice) and instructions (task-related, phenomenological, standard). Participants viewed photos of targets and made identification decisions about a lineup for each target. Instructions about memory phenomenology improved discriminability in delayed-choice lineups, while task-related instructions were ineffective. Metacognitive instructions about how to better evaluate memory quality in modified lineup tasks could improve recollection for greater identification accuracy even when memory is poor. While immediate post-decision confidence is a good predictor of identification accuracy, lineup modifications that improve eyewitness memory use would provide better evidence of suspect guilt or innocence. We discuss implications for lineup theory and design.

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Αναγνώριση σημαίνει ενοχή; Mια ανασκόπηση των παραγόντων επιρροής της επίδοσης των αυτοπτών μαρτύρων

Psychology: the Journal of the Hellenic Psychological Society ◽

10.12681/psy_hps.23608 ◽

2020 ◽

Vol 19 (1) ◽

pp. 63

Author(s):

Άννα Σαγανά ◽

Melanie Sauerland

Keyword(s):

Present Article ◽

Eyewitness Identification ◽

Research Community ◽

Judicial System ◽

Identification Accuracy ◽

Identification Performance ◽

Wrongful Convictions ◽

The Core ◽

System Variables

Eyewitness identification stands as one of the core aspects of the judicial system. However, when it comes to identifying faces, people often make mistakes. Thus, it should not come as a surprise that eyewitness identification has been shown to be the number one factor of wrongful convictions (www.innoccenceproject.org). Therefore it is importantto understand the reasons that make eyewitnesses so error prone and investigate how we could enhance their performance. In the present article we examine the factors that have an impact on eyewitnessidentification performance. More specifically, we will refer to those variables over which the research community has reached consensus. These include estimator and system variables as well as postdictors,which are variables capable to diagnose the identification accuracy once it has taken place. In doing so we aim to reveal those parameters that are based on a sturdy research base, but have notwithstanding beenneglected by the Greek judicial system. We suggest a number of alterations and improvements, based on this research basis that can improve identification performance.

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A Novel Auditory Display for Neonatal Resuscitation: Laboratory Studies Simulating Pulse Oximetry in the First 10 Minutes After Birth

Human Factors The Journal of the Human Factors and Ergonomics Society ◽

10.1177/0018720818793769 ◽

2018 ◽

Vol 61 (1) ◽

pp. 119-138 ◽

Cited By ~ 4

Author(s):

Jelena Zestic ◽

Birgit Brecknell ◽

Helen Liley ◽

Penelope Sanderson

Keyword(s):

Oxygen Saturation ◽

Pulse Oximetry ◽

Neonatal Resuscitation ◽

Identification Accuracy ◽

Target Range ◽

Distractor Task ◽

Auditory Display ◽

Laboratory Studies ◽

Arithmetic Task ◽

Range Change

Objective: We tested whether enhanced sonifications would improve participants’ ability to judge the oxygen saturation levels (SpO2) of simulated neonates in the first 10 min after birth. Background: During the resuscitation of a newborn infant, clinicians must keep the neonate’s SpO2 levels within the target range, however the boundaries for the target range change each minute during the first 10 min after birth. Resuscitation places significant demand on the clinician’s visual attention, and the pulse oximeter’s sonification could provide eyes-free monitoring. However, clinicians have difficulty judging SpO2 levels using the current sonification. Method: In two experiments, nonclinicians’ ability to detect SpO2 range and direction—while performing continuous arithmetic problems—was tested with enhanced versus conventional sonifications. In Experiment 1, tremolo signaled when SpO2 had deviated below or above the target range. In Experiment 2, tremolo plus brightness signaled when SpO2 was above target range, and tremolo alone when SpO2 was below target range. Results: The tremolo sonification improved range identification accuracy over the conventional display (81% vs. 63%, p < .001). The tremolo plus brightness sonification further improved range identification accuracy over the conventional display (92% vs. 62%, p <.001). In both experiments, there was no difference across conditions in arithmetic task accuracy ( p >.05). Conclusion: Using the enhanced sonifications, participants identified SpO2 range more accurately despite a continuous distractor task. Application: An enhanced pulse oximetry sonification could help clinicians multitask more effectively during neonatal resuscitations.

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