Human height estimation from highly distorted surveillance image
dc.accessRights | Anonymous | * |
dc.contributor.author | Tosti, Francesco | |
dc.contributor.author | Nardinocchi, Carla | |
dc.contributor.author | Ciampini, Claudio | |
dc.contributor.author | Marsella, Maria | |
dc.contributor.author | Lopes, Pierpaolo | |
dc.contributor.author | Giuliani, Samuele | |
dc.contributor.author | Wahbeh, Wissam | |
dc.date.accessioned | 2023-06-19T12:05:23Z | |
dc.date.available | 2022-04-22T06:00:42Z | |
dc.date.available | 2023-06-19T12:05:23Z | |
dc.date.issued | 2021-10-01 | |
dc.description.abstract | Video surveillance camera (VSC) is an important source of information during inves- tigations especially if used as a tool for the extraction of verified and reliable foren- sic measurements. In this study, some aspects of human height extraction from VSC video frames are analyzed with the aim of identifying and mitigating error sources that can strongly affect the measurement. More specifically, those introduced by lens distortion are present in wide-field-of-view lens such as VSCs. A weak model, which is not able to properly describe and correct the lens distortion, could introduce sys- tematic errors. This study focuses on the aspect of camera calibration to verify human height extraction by Amped FIVE software, which is adopted by the Forensic science laboratories of Carabinieri Force (RaCIS), Italy. A stable and reliable approach of cam- era calibration is needed since investigators have to deal with different cameras while inspecting the crime scene. The performance of the software in correcting distorted images is compared with a technique of single view self-calibration. Both approaches were applied to several frames acquired by a fish-eye camera and then measuring the height of five different people. Moreover, two actual cases, both characterized by common low-resolution and distorted images, were also analyzed. The height of four known persons was measured and used as reference value for validation. Results show no significant difference between the two calibration approaches working with fish-eye camera in test field, while evidence of differences was found in the measure- ment on the actual cases. | en_US |
dc.identifier.issn | 0022-1198 | |
dc.identifier.issn | 1556-4029 | |
dc.identifier.uri | https://doi.org/10.26041/fhnw-4160 | |
dc.identifier.uri | https://irf.fhnw.ch/handle/11654/33443 | |
dc.issue | 1 | en_US |
dc.language.iso | en | en_US |
dc.publisher | Wiley | en_US |
dc.relation.ispartof | Journal of Forensic Sciences | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.subject | Camera calibration | en_US |
dc.subject | Height measurements | en_US |
dc.subject | Image distortion | en_US |
dc.subject | Photogrammetry | en_US |
dc.subject | Space resection | en_US |
dc.subject | Terrestrial laser scanner | en_US |
dc.subject | Vanishing line and point | en_US |
dc.subject.ddc | 600 - Technik, Medizin, angewandte Wissenschaften | en_US |
dc.title | Human height estimation from highly distorted surveillance image | en_US |
dc.type | 01A - Beitrag in wissenschaftlicher Zeitschrift | * |
dc.volume | 67 | en_US |
dspace.entity.type | Publication | |
fhnw.InventedHere | Yes | en_US |
fhnw.IsStudentsWork | no | en_US |
fhnw.ReviewType | Anonymous ex ante peer review of a complete publication | en_US |
fhnw.affiliation.hochschule | Hochschule für Architektur, Bau und Geomatik FHNW | de_CH |
fhnw.affiliation.institut | Institut Digitales Bauen | de_CH |
fhnw.openAccessCategory | Hybrid | en_US |
fhnw.pagination | 332-344 | en_US |
fhnw.publicationState | Unpublished | en_US |
relation.isAuthorOfPublication | a9f64384-ab8c-404c-8601-f76efa850ab3 | |
relation.isAuthorOfPublication.latestForDiscovery | a9f64384-ab8c-404c-8601-f76efa850ab3 |
Dateien
Originalbündel
1 - 1 von 1
- Name:
- 2021_JFS_Human height estimation from cameras.pdf
- Größe:
- 2.17 MB
- Format:
- Adobe Portable Document Format
- Beschreibung:
Lizenzbündel
1 - 1 von 1
Kein Vorschaubild vorhanden
- Name:
- license.txt
- Größe:
- 1.37 KB
- Format:
- Item-specific license agreed upon to submission
- Beschreibung: