| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | sibgrapi.sid.inpe.br | |||
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH | |||
| Identifier | 8JMKD3MGPEW34M/45CKFQB | |||
| Repository | sid.inpe.br/sibgrapi/2021/09.04.19.00 | |||
| Last Update | 2021:09.06.14.47.39 (UTC) administrator | |||
| Metadata Repository | sid.inpe.br/sibgrapi/2021/09.04.19.00.11 | |||
| Metadata Last Update | 2022:06.14.00.00.24 (UTC) administrator | |||
| DOI | 10.1109/SIBGRAPI54419.2021.00041 | |||
| Citation Key | MenezesFerrPereGome:2021:BiFaFa | |||
| Title | Bias and Fairness in Face Detection  | |||
| Format | On-line | |||
| Year | 2021 | |||
| Access Date | 2024, May 06 | |||
| Number of Files | 1 | |||
| Size | 496 KiB | |||
| 2. Context | ||||
| Author | 1 Menezes, Hanna França 2 Ferreira, Arthur Silva Cavalcante 3 Pereira, Eanes Torres 4 Gomes, Herman Martins | |||
| Affiliation | 1 Universidade Federal de Campina Grande 2 Universidade Federal de Campina Grande 3 Universidade Federal de Campina Grande 4 Universidade Federal de Campina Grande | |||
| Editor | Paiva, Afonso Menotti, David Baranoski, Gladimir V. G. Proença, Hugo Pedro Junior, Antonio Lopes Apolinario Papa, João Paulo Pagliosa, Paulo dos Santos, Thiago Oliveira e Sá, Asla Medeiros da Silveira, Thiago Lopes Trugillo Brazil, Emilio Vital Ponti, Moacir A. Fernandes, Leandro A. F. Avila, Sandra | |||
| e-Mail Address | hanna@copin.ufcg.edu.br | |||
| Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) | |||
| Conference Location | Gramado, RS, Brazil (virtual) | |||
| Date | 18-22 Oct. 2021 | |||
| Publisher | IEEE Computer Society | |||
| Publisher City | Los Alamitos | |||
| Book Title | Proceedings | |||
| Tertiary Type | Full Paper | |||
| History (UTC) | 2021-09-06 14:47:40 :: hanna@copin.ufcg.edu.br -> administrator :: 2021 2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021 2022-03-02 13:31:43 :: menottid@gmail.com -> administrator :: 2021 2022-06-14 00:00:24 :: administrator -> :: 2021 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Version Type | finaldraft | |||
| Keywords | Bias Fairness Face Detection | |||
| Abstract | Processing of face images is used in many areas, for example: commercial applications such as video-games; facial biometrics; facial expression recognition, etc. Face detection is a crucial step for any system that processes face images. Therefore, if there is bias or unfairness in this first step, all the processing steps that follow may be compromised. Errors in automatic face detection may be harmful to people as, for instance, in situations where a decision may limit or restrict their freedom to come and go. Therefore, it is crucial to investigate the existence of these errors caused due to bias or unfairness. In this paper, an analysis of five well-known top accuracy face detectors is performed to investigate the presence of bias and unfairness in their results. Some of the metrics used to identify the existence of bias and unfairness involved the verification of demographic parity, verification of existence of false positives and/or false negatives, rate of positive prediction, and verification of equalized odds. Data from about 365 different individuals were randomly selected from the Facebook Casual Conversations Dataset, resulting in approximately 5,500 videos, providing 550,000 frames used for face detection in the performed experiments. The obtained results show that all five face detectors presented a high risk of not detecting faces from the female gender and from people between 46 and 85 years old. Furthermore, the skin tone groups related with dark skin are the groups pointed out with highest risk of faces not being detected for four of the five evaluated face detectors. This paper points out the necessity of the research community to engage in breaking the perpetuation of injustice that may be present in datasets or machine learning models. | |||
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Bias and Fairness... | |||
| Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Bias and Fairness... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
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| 4. Conditions of access and use | ||||
| data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/45CKFQB | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45CKFQB | |||
| Language | en | |||
| Target File | 103.pdf | |||
| User Group | hanna@copin.ufcg.edu.br | |||
| Visibility | shown | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 | |||
| Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS 8JMKD3MGPEW34M/4742MCS | |||
| Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 4 | |||
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 | |||
| 6. Notes | ||||
| Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume | |||