| dc.creator | Delibasis K.K., Goudas T., Maglogiannis I. | en |
| dc.date.accessioned | 2023-01-31T07:53:02Z | |
| dc.date.available | 2023-01-31T07:53:02Z | |
| dc.date.issued | 2015 | |
| dc.identifier | 10.1145/2769493.2769518 | |
| dc.identifier.isbn | 9781450334525 | |
| dc.identifier.uri | http://hdl.handle.net/11615/73186 | |
| dc.description.abstract | In this work we propose a novel algorithm for human silhouette segmentation, which combines characteristics from a number of well established and state of the art algorithms, such as the Gaussian mixture models, the Self Organizing Maps and the Illumination Sensitive method. The proposed algorithm is evaluated against user-defined ground truth segmentation for two different types of indoor video sequences, one of which was obtained by a hemispheric camera. The behavior of the algorithm with respect to its controlling parameters is investigated and its computational burden is studied. © 2015 ACM. | en |
| dc.language.iso | en | en |
| dc.source | 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2015 - Proceedings | en |
| dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957001238&doi=10.1145%2f2769493.2769518&partnerID=40&md5=8fc951c6f936080bba18a5109a8cf813 | |
| dc.subject | Conformal mapping | en |
| dc.subject | Self organizing maps | en |
| dc.subject | Activity detection | en |
| dc.subject | Background model | en |
| dc.subject | Computational burden | en |
| dc.subject | Controlling parameters | en |
| dc.subject | Gaussian Mixture Model | en |
| dc.subject | Multiple backgrounds | en |
| dc.subject | State-of-the-art algorithms | en |
| dc.subject | Video segmentation | en |
| dc.subject | Algorithms | en |
| dc.subject | Association for Computing Machinery, Inc | en |
| dc.title | A novel hybrid approach for human silhouette segmentation | en |
| dc.type | conferenceItem | en |