| Revista: | Boletim de ciencias geodesicas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000457302 |
| ISSN: | 1413-4853 |
| Autores: | Amisse, Caisse1 Palma, Mario Ernesto Jijon1 Centeno, Jorge Antonio Silva1 |
| Instituciones: | 1Universidade Federal do Parana, Programa de Pos-graduacao em Ciencias Geodesicas, Curitiba, Parana. Brasil 2Universidade Rovuma, Departamento de Ciencias Naturais, Nampula. Mozambique |
| Año: | 2021 |
| Volumen: | 27 |
| Número: | 3 |
| País: | Brasil |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico, descriptivo |
| Resumen en inglés | The wide use of cameras enables the availability of a large amount of image frames that can be used for people counting or to monitor crowds or single individuals for security purposes. These applications require both, object detection and tracking. This task has shown to be challenging due to problems such as occlusion, deformation, motion blur, and scale variation. One alternative to perform tracking is based on the comparison of features extracted for the individual objects from the image. For this purpose, it is necessary to identify the object of interest, a human image, from the rest of the scene. This paper introduces a method to perform the separation of human bodies from images with changing backgrounds. The method is based on image segmentation, the analysis of the possible pose, and a final refinement step based on probabilistic relaxation. It is the first work we are aware that probabilistic fields computed from human pose figures are combined with an improvement step of relaxation for pedestrian segmentation. The proposed method is evaluated using different image series and the results show that it can work efficiently, but it is dependent on some parameters to be set according to the image contrast and scale. Tests show accuracies above 71%. The method performs well in other datasets, where it achieves results comparable to state-of-the-art approaches |
| Disciplinas: | Geociencias |
| Palabras clave: | Geodesia, Peatones, Procesamiento de imágenes, Segmentación de peatones, Relajación probabilística |
| Keyword: | Geodesy, Pedestrians, Image processing, Pedestrian segmentation, Probabilistic relaxation |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
