Dataset Information

Evaluation of Camera Recognition Performance under Blockage Using Virtual Test Drive Toolchain.

ABSTRACT: This study is the first to develop technology to evaluate the object recognition performance of camera sensors, which are increasingly important in autonomous vehicles owing to their relatively low price, and to verify the efficiency of camera recognition algorithms in obstruction situations. To this end, the concentration and color of the blockage and the type and color of the object were set as major factors, with their effects on camera recognition performance analyzed using a camera simulator based on a virtual test drive toolkit. The results show that the blockage concentration has the largest impact on object recognition, followed in order by the object type, blockage color, and object color. As for the blockage color, black exhibited better recognition performance than gray and yellow. In addition, changes in the blockage color affected the recognition of object types, resulting in different responses to each object. Through this study, we propose a blockage-based camera recognition performance evaluation method using simulation, and we establish an algorithm evaluation environment for various manufacturers through an interface with an actual camera. By suggesting the necessity and timing of future camera lens cleaning, we provide manufacturers with technical measures to improve the cleaning timing and camera safety.

SUBMITTER: Son S

PROVIDER: S-EPMC10575171 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Evaluation of Camera Recognition Performance under Blockage Using Virtual Test Drive Toolchain.

Son Sungho S Lee Woongsu W Jung Hyungi H Lee Jungki J Kim Charyung C Lee Hyunwoo H Park Hyungwon H Lee Hyunmi H Jang Jeongah J Cho Sungwan S Ryu Han-Cheol HC

Sensors (Basel, Switzerland) 20230922 19

This study is the first to develop technology to evaluate the object recognition performance of camera sensors, which are increasingly important in autonomous vehicles owing to their relatively low price, and to verify the efficiency of camera recognition algorithms in obstruction situations. To this end, the concentration and color of the blockage and the type and color of the object were set as major factors, with their effects on camera recognition performance analyzed using a camera simulato ...[more]

PMID: 37836857

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Project description:The purpose of this study was (1) to implement a test for binocular imbalance in a Virtual Reality headset, (2) to assess its testability, reliability and outcomes in a population of clinical patients and (3) to evaluate the relationships of interocular acuity difference, stereoacuity and binocular imbalance to amblyogenic risk factors. 100 volunteers (6 to 70 years old, mean 21.2 ± 16.2), 21 with no amblyogenic risk factors and 79 with amblyopia or a history of amblyopia participated. Participants were classified by amblyogenic risk factor (24 anisometropic, 25 strabismic and 30 mixed) and, for those with strabismus, also by refractive response (16 accommodative and 39 non-accommodative). We characterized our sample using three variables, called the 'triplet' henceforth: interocular acuity difference, stereoacuity and imbalance factor. Binocular imbalance showed high test-retest reliability (no significant difference between test and retest in a subgroup, n = 20, p = 0.831); was correlated with Worth 4 dots test (r = 0.538, p<0.0001); and correlated with both interocular acuity difference (r = 0.575, p<0.0001) and stereoacuity (r = 0.675, p<0.0001). The mean values of each variable of the triplet differed depending on group classification. Mixed and non-accommodative groups showed the worst mean values compared with the other groups. Among participants with strabismus, strabismic vs mixed subgroups did not show significant differences in any variable of the triplet, whereas the accommodative vs non-accommodative subgroups showed significant differences in all of them. According to a univariate logistic model, any variable of the triplet provides a good metric for differentiating patients from controls, except for binocular imbalance for anisometropic subgroup. The proposed binocular imbalance test is feasible and reliable. We recommend monitoring amblyopia clinically not only considering visual acuity, but also stereoacuity and interocular imbalance. Stereoacuity on its own fails because of the high percentage of patients with no measurable stereoacuity. Binocular imbalance may help to fill that gap.

Project description:Rapid diagnostic tests (RDTs) for SARS-CoV-2 antigens (Ag) that can be performed at point of care (POC) can supplement molecular testing and help mitigate the COVID-19 pandemic. Deployment of an Ag RDT requires an understanding of its operational and performance characteristics under real-world conditions and in relevant subpopulations. We evaluated the Abbott BinaxNOW COVID-19 Ag card in a high-throughput, drive-through, free community testing site in Massachusetts using anterior nasal (AN) swab reverse transcriptase PCR (RT-PCR) for clinical testing. Individuals presenting for molecular testing in two of seven lanes were offered the opportunity to also receive BinaxNOW testing. Dual AN swabs were collected from symptomatic and asymptomatic children (≤18 years of age) and adults. BinaxNOW testing was performed in a testing pod with temperature/humidity monitoring. One individual performed testing and official result reporting for each test, but most tests had a second independent reading to assess interoperator agreement. Positive BinaxNOW results were scored as faint, medium, or strong. Positive BinaxNOW results were reported to patients by phone, and they were instructed to isolate pending RT-PCR results. The paired RT-PCR result was the reference for sensitivity and specificity calculations. Of 2,482 participants, 1,380 adults and 928 children had paired RT-PCR/BinaxNOW results and complete symptom data. In this study, 974/1,380 (71%) adults and 829/928 (89%) children were asymptomatic. BinaxNOW had 96.5% (95% confidence interval [CI], 90.0 to 99.3) sensitivity and 100% (95% CI, 98.6 to 100.0) specificity in adults within 7 days of symptoms and 84.6% (95% CI, 65.1 to 95.6) sensitivity and 100% (95% CI, 94.5 to 100.0) specificity in children within 7 days of symptoms. Sensitivity and specificity in asymptomatic adults were 70.2% (95% CI, 56.6 to 81.6) and 99.6% (95% CI, 98.9 to 99.9), respectively, and in asymptomatic children, they were 65.4% (95% CI, 55.6 to 74.4) and 99.0% (95% CI, 98.0 to 99.6), respectively. By cycle threshold (CT ) value cutoff, sensitivity in all subgroups combined (n = 292 RT-PCR-positive individuals) was 99.3% with CT values of ≤25, 95.8% with CT values of ≤30, and 81.2% with CT values of ≤35. Twelve false-positive BinaxNOW results (out of 2,308 tests) were observed; in all 12, the test bands were faint but otherwise normal and were noted by both readers. One invalid BinaxNOW result was identified. Interoperator agreement (positive versus negative BinaxNOW result) was 100% (n = 2,230/2,230 double reads). Each operator was able to process 20 RDTs per hour. In a separate set of 30 specimens (from individuals with symptoms ≤7 days) run at temperatures below the manufacturer's recommended range (46 to 58.5°F), sensitivity was 66.7% and specificity 95.2%. BinaxNOW had very high specificity in both adults and children and very high sensitivity in newly symptomatic adults. Overall, 95.8% sensitivity was observed with CT values of ≤30. These data support public health recommendations for use of the BinaxNOW test in adults with symptoms for ≤7 days without RT-PCR confirmation. Excellent interoperator agreement indicates that an individual can perform and read the BinaxNOW test alone. A skilled laboratorian can perform and read 20 tests per hour. Careful attention to temperature is critical.

Project description:BackgroundTo facilitate deployment of point-of-care testing for severe acute respiratory syndrome coronavirus 2, we evaluated the Access Bio CareStart COVID-19 Antigen test in a high-throughput, drive-through, free community testing site using anterior nasal (AN) swab reverse-transcription polymerase chain reaction (RT-PCR) for clinical testing.MethodsConsenting symptomatic and asymptomatic children (≤18 years) and adults received dual AN swabs. CareStart testing was performed with temperature/humidity monitoring. All tests had 2 independent reads to assess interoperator agreement. Patients with positive CareStart results were called and instructed to isolate pending RT-PCR results. The paired RT-PCR result was the reference for sensitivity and specificity calculations.ResultsOf 1603 participants, 1245 adults and 253 children had paired RT-PCR/CareStart results and complete symptom data. Eighty-three percent of adults and 87% of children were asymptomatic. CareStart sensitivity/specificity were 84.8% (95% confidence interval [CI], 71.1-93.7)/97.2% (95% CI, 92.0-99.4) and 85.7% (95% CI, 42.1-99.6)/89.5% (95% CI, 66.9-98.7) in adults and children, respectively, within 5 days of symptoms. Sensitivity/specificity were 50.0% (95% CI, 41.0-59.0)/99.1% (95% CI, 98.3-99.6) in asymptomatic adults and 51.4% (95% CI, 34.4-68.1)/97.8% (95% CI, 94.5-99.4) in asymptomatic children. Sensitivity in all 234 RT-PCR-positive people was 96.3% with cycle threshold (Ct) ≤25, 79.6% with Ct ≤30, and 61.4% with Ct ≤35. All 21 false-positive CareStart tests had faint but normal bands. Interoperator agreement was 99.5%. Operational challenges included identification of faint test bands and inconsistent swab elution volumes.ConclusionsCareStart had high sensitivity in people with Ct ≤25 and moderate sensitivity in symptomatic people overall. Specificity was unexpectedly lower in symptomatic versus asymptomatic people. Excellent interoperator agreement was observed, but operational challenges indicate that operator training is warranted.

Dataset Information

Evaluation of Camera Recognition Performance under Blockage Using Virtual Test Drive Toolchain.

Publications

Evaluation of Camera Recognition Performance under Blockage Using Virtual Test Drive Toolchain.

Similar Datasets

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