Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/44013
Título: | Automatic scene calibration for detecting and tracking people using a single camera | Autores/as: | Perdomo, David Alonso, Jesús B. Travieso, Carlos M. Ferrer, Miguel A. |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | People tracking, Multiple people segmentation, Active vision, Surveillance, Scene calibration | Fecha de publicación: | 2013 | Editor/a: | 0952-1976 | Publicación seriada: | Engineering Applications of Artificial Intelligence | Resumen: | Segmenting and tracking of people is an important aim in the video analysis with multitudinous applications. The scene calibration enables the system to process the input video in a different way depending on the camera position and the scene characteristics for arising the successful results. In complex situations there exists extended occlusions, shadows and/or rejections, so that an appropriate calibration is required in order to achieve a highly developed people's segmentation as well as a tracking algorithm. In the majority of cases, once the system has been installed in a certain scene, it is difficult to obtain the calibration information of the scene. In this paper, an automatic method to calibrate the scene for detecting and tracking people systems is presented based on measurements of video sequences captured from a stationary camera. | URI: | http://hdl.handle.net/10553/44013 | ISSN: | 0952-1976 | DOI: | 10.1016/j.engappai.2012.08.009 | Fuente: | Engineering Applications of Artificial Intelligence[ISSN 0952-1976],v. 26, p. 924-935 |
Colección: | Artículos |
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