Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Verlekar, T. T., Soares, L. D. & Correia, P. L. (2017). Shadow type identification for gait recognition using shadows. In 23rd Portuguese Conference on Pattern Recognition, RECPAD. (pp. 73-74). Amadora: APRP.
Exportar Referência (IEEE)
T. T. Verlekar et al.,  "Shadow type identification for gait recognition using shadows", in 23rd Portuguese Conf. on Pattern Recognition, RECPAD, Amadora, APRP, 2017, pp. 73-74
Exportar BibTeX
@inproceedings{verlekar2017_1714889448492,
	author = "Verlekar, T. T. and Soares, L. D. and Correia, P. L.",
	title = "Shadow type identification for gait recognition using shadows",
	booktitle = "23rd Portuguese Conference on Pattern Recognition, RECPAD",
	year = "2017",
	editor = "",
	volume = "",
	number = "",
	series = "",
	pages = "73-74",
	publisher = "APRP",
	address = "Amadora",
	organization = ""
}
Exportar RIS
TY  - CPAPER
TI  - Shadow type identification for gait recognition using shadows
T2  - 23rd Portuguese Conference on Pattern Recognition, RECPAD
AU  - Verlekar, T. T.
AU  - Soares, L. D.
AU  - Correia, P. L.
PY  - 2017
SP  - 73-74
CY  - Amadora
AB  - \Using features acquired from the shadow cast by a walking person can be an alternative for gait recognition whenever the person’s body is occluded, such as when capturing images from an overhead position. However, the shadow, depending on the light source characteristics, can be cast as a blob with no distinguishing characteristics. Most state-of-the-art methods fail in the presence of such “diffused” shadows. Thus, this paper presents a novel method to identify the type of shadow cast by a person. The proposed method generates a histogram of the intensity ratio between foreground and background areas, whose analysis allows identifying the type of shadow cast by the person. The proposed method is very promising, achieving a 90% correct shadow type identification with the dataset tested.
ER  -