HOPBAS10K: A 98×98 Pixels CMOS Vision Sensor for Background Subtraction
| dc.contributor.affiliation | Universidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS) | |
| dc.contributor.affiliation | Universidade de Santiago de Compostela. Departamento de Electrónica e Computación | |
| dc.contributor.author | García Lesta, Daniel | |
| dc.contributor.author | Cabello Ferrer, Diego | |
| dc.contributor.author | López Martínez, Paula | |
| dc.contributor.author | Brea Sánchez, Víctor Manuel | |
| dc.date.accessioned | 2024-11-21T10:05:21Z | |
| dc.date.available | 2024-11-21T10:05:21Z | |
| dc.date.issued | 2024-02-26 | |
| dc.description | © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
| dc.description.abstract | Background subtraction is one of the first visual tasks in many video processing applications. In this work, we introduce a hardware adaptation of a top-ranked rule-based algorithm, the Pixel-Based Adaptive Segmenter (PBAS), implemented on an integrated circuit with on-focal plane processing. On average, our hardware-oriented PBAS (HO-PBAS) proposal features a similar algorithm performance to that of the original PBAS with the benefit of a reduced number of samples of the background model and linear equations, and thus a simpler overall model. This algorithm was implemented as a 98×98 pixels full-custom mixed-signal 180 nm standard CMOS vision sensor. This solution features in-pixel processing with resource sharing strategies and 47 μm pixel pitch. The in-pixel processing includes the whole algorithm data path along with image pre-processing. The assessment of our implementation through F-Measure metrics with images captured by our chip from the public dataset changedetection shown on a PC screen results in a decrease of performance of only 6.7% with respect to the software version of PBAS. | |
| dc.description.peerreviewed | SI | |
| dc.description.sponsorship | This work has received funding from projects PID2021-128009OBC32, from the MCIN/AEI/10.13039/501100011033 and FEDER; and the European Union (European Regional Development Fund): from the Xunta de Galicia-Conseller´ıa de Cultura, Educacion e Ordenaci ´ on´ Universitaria Accreditation 2019–2022 ED431G-2019/04 and Reference Competitive Group Accreditation 2021–2024, GRC2021/48. | |
| dc.identifier.citation | IEEE Sensors Journal (Volume: 24, Issue: 7, 01 April 2024) | |
| dc.identifier.doi | 10.1109/JSEN.2024.3367169 | |
| dc.identifier.issn | 1558-1748 | |
| dc.identifier.uri | https://hdl.handle.net/10347/37790 | |
| dc.issue.number | 7 | |
| dc.journal.title | IEEE Sensors Journal | |
| dc.language.iso | eng | |
| dc.page.final | 11935 | |
| dc.page.initial | 11927 | |
| dc.publisher | IEEE | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-128009OB-I00/ES/INTELIGENCIA ARTIFICIAL EN EL BORDE: SOLUCIONES EMBEBIDAS DE BAJO CONSUMO DE POTENCIA/ | |
| dc.relation.publisherversion | https://ieeexplore.ieee.org/document/10445312 | |
| dc.rights.accessRights | open access | |
| dc.subject | Background subtraction | |
| dc.subject | CMOS Vision Sensors | |
| dc.subject | PBAS | |
| dc.subject | Mixed-signal | |
| dc.title | HOPBAS10K: A 98×98 Pixels CMOS Vision Sensor for Background Subtraction | |
| dc.type | journal article | |
| dc.type.hasVersion | AM | |
| dc.volume.number | 24 | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 0d74337a-b632-4ad6-8713-6db5c1a0d643 | |
| relation.isAuthorOfPublication | e78a1e57-0d7c-4392-8e16-b2b0e1d64823 | |
| relation.isAuthorOfPublication | 22d4aeb8-73ba-4743-a84e-9118799ab1f2 | |
| relation.isAuthorOfPublication.latestForDiscovery | 0d74337a-b632-4ad6-8713-6db5c1a0d643 |
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