Partially obscured human detection based on component detectors using multiple feature descriptors
This paper presents a human detection system based on component detector using multiple feature descriptors. The contribution presents two issues for dealing with the problem of partially obscured human. First, it presents the extension of feature descriptors using multiple scales based Histograms o...
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| Other Authors: | , |
| Format: | article |
| Language: | English |
| Published: |
2014
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| Online Access: | http://ridda2.utp.ac.pa/handle/123456789/5088 |
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| _version_ | 1869451861669445632 |
|---|---|
| author | Cáceres Hernández, Danilo |
| author2 | Hyun Jo, Kang Dung Hoang, Van |
| author2_role | author author |
| author_browse | Cáceres Hernández, Danilo Dung Hoang, Van Hyun Jo, Kang |
| author_facet | Cáceres Hernández, Danilo Hyun Jo, Kang Dung Hoang, Van |
| author_role | author |
| collection | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| dc.creator.none.fl_str_mv | Cáceres Hernández, Danilo Hyun Jo, Kang Dung Hoang, Van |
| dc.date.none.fl_str_mv | 2014-08-03 2014-08-03 2018-06-28T21:15:27Z 2018-06-28T21:15:27Z 2018-06-28T21:15:27Z 2018-06-28T21:15:27Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://ridda2.utp.ac.pa/handle/123456789/5088 http://ridda2.utp.ac.pa/handle/123456789/5088 |
| dc.language.none.fl_str_mv | eng eng |
| dc.rights.none.fl_str_mv | https://creativecommons.org/licenses/by-nc-sa/4.0/ info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP instname:Universidad Tecnológica de Panamá instacron:U Tecnológica de Panamá |
| dc.subject.none.fl_str_mv | Boosting machines parallelogram based Haar-like feature multiple scale block based HOG features support vector machine Boosting machines parallelogram based Haar-like feature multiple scale block based HOG features support vector machine |
| dc.title.none.fl_str_mv | Partially obscured human detection based on component detectors using multiple feature descriptors |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | This paper presents a human detection system based on component detector using multiple feature descriptors. The contribution presents two issues for dealing with the problem of partially obscured human. First, it presents the extension of feature descriptors using multiple scales based Histograms of Oriented Gradients (HOG) and parallelogram based Haar-like feature (PHF) for improving the accuracy of the system. By using multiple scales based HOG, an extensive feature space allows obtaining high-discriminated features. Otherwise, the PHF is adaptive limb shapes of human in fast computing feature. Second, learning system using boosting classifications based approach is used for training and detecting the partially obscured human. The advantage of boosting is constructing a strong classification by combining a set of weak classifiers. However, the performance of boosting depends on the kernel of weak classifier. Therefore, the hybrid algorithms based on AdaBoost and SVM using the proposed feature descriptors is one of solutions for robust human detection. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | PA_7ea0e8b25d41c7ca401c8f4f61354e62 |
| instacron_str | U Tecnológica de Panamá |
| institution | U Tecnológica de Panamá |
| instname_str | Universidad Tecnológica de Panamá |
| language | eng |
| network_acronym_str | PA |
| network_name_str | oai la ref anni2 |
| oai_identifier_str | oai:ridda2.utp.ac.pa:123456789/5088 |
| publishDate | 2014 |
| publishDateSort | 2014 |
| reponame_str | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | https://creativecommons.org/licenses/by-nc-sa/4.0/ |
| spelling | Partially obscured human detection based on component detectors using multiple feature descriptorsCáceres Hernández, DaniloHyun Jo, KangDung Hoang, VanBoosting machinesparallelogram based Haar-like featuremultiple scale block based HOG featuressupport vector machineBoosting machinesparallelogram based Haar-like featuremultiple scale block based HOG featuressupport vector machineThis paper presents a human detection system based on component detector using multiple feature descriptors. The contribution presents two issues for dealing with the problem of partially obscured human. First, it presents the extension of feature descriptors using multiple scales based Histograms of Oriented Gradients (HOG) and parallelogram based Haar-like feature (PHF) for improving the accuracy of the system. By using multiple scales based HOG, an extensive feature space allows obtaining high-discriminated features. Otherwise, the PHF is adaptive limb shapes of human in fast computing feature. Second, learning system using boosting classifications based approach is used for training and detecting the partially obscured human. The advantage of boosting is constructing a strong classification by combining a set of weak classifiers. However, the performance of boosting depends on the kernel of weak classifier. Therefore, the hybrid algorithms based on AdaBoost and SVM using the proposed feature descriptors is one of solutions for robust human detection.This paper presents a human detection system based on component detector using multiple feature descriptors. The contribution presents two issues for dealing with the problem of partially obscured human. First, it presents the extension of feature descriptors using multiple scales based Histograms of Oriented Gradients (HOG) and parallelogram based Haar-like feature (PHF) for improving the accuracy of the system. By using multiple scales based HOG, an extensive feature space allows obtaining high-discriminated features. Otherwise, the PHF is adaptive limb shapes of human in fast computing feature. Second, learning system using boosting classifications based approach is used for training and detecting the partially obscured human. The advantage of boosting is constructing a strong classification by combining a set of weak classifiers. However, the performance of boosting depends on the kernel of weak classifier. Therefore, the hybrid algorithms based on AdaBoost and SVM using the proposed feature descriptors is one of solutions for robust human detection.2018-06-28T21:15:27Z2018-06-28T21:15:27Z2018-06-28T21:15:27Z2018-06-28T21:15:27Z2014-08-032014-08-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://ridda2.utp.ac.pa/handle/123456789/5088http://ridda2.utp.ac.pa/handle/123456789/5088engenghttps://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccessreponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáoai:ridda2.utp.ac.pa:123456789/50882021-07-06T15:34:54Z |
| spellingShingle | Partially obscured human detection based on component detectors using multiple feature descriptors Cáceres Hernández, Danilo Boosting machines parallelogram based Haar-like feature multiple scale block based HOG features support vector machine Boosting machines parallelogram based Haar-like feature multiple scale block based HOG features support vector machine |
| status_str | publishedVersion |
| title | Partially obscured human detection based on component detectors using multiple feature descriptors |
| title_full | Partially obscured human detection based on component detectors using multiple feature descriptors |
| title_fullStr | Partially obscured human detection based on component detectors using multiple feature descriptors |
| title_full_unstemmed | Partially obscured human detection based on component detectors using multiple feature descriptors |
| title_short | Partially obscured human detection based on component detectors using multiple feature descriptors |
| title_sort | Partially obscured human detection based on component detectors using multiple feature descriptors |
| topic | Boosting machines parallelogram based Haar-like feature multiple scale block based HOG features support vector machine Boosting machines parallelogram based Haar-like feature multiple scale block based HOG features support vector machine |
| url | http://ridda2.utp.ac.pa/handle/123456789/5088 |