A Study of Feature Combination for Vehicle Detection Based on Image Processing
Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work report...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/196251 |
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| _version_ | 1850235998768726016 |
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| author | Jon Arróspide Luis Salgado |
| author_facet | Jon Arróspide Luis Salgado |
| author_sort | Jon Arróspide |
| collection | DOAJ |
| description | Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification. |
| format | Article |
| id | doaj-art-19b17b36a5444095ae8ef95fbcd4e850 |
| institution | OA Journals |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-19b17b36a5444095ae8ef95fbcd4e8502025-08-20T02:02:05ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/196251196251A Study of Feature Combination for Vehicle Detection Based on Image ProcessingJon Arróspide0Luis Salgado1Grupo de Tratamiento de Imágenes, Universidad Politécnica de Madrid, 28040 Madrid, SpainGrupo de Tratamiento de Imágenes, Universidad Politécnica de Madrid, 28040 Madrid, SpainVideo analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification.http://dx.doi.org/10.1155/2014/196251 |
| spellingShingle | Jon Arróspide Luis Salgado A Study of Feature Combination for Vehicle Detection Based on Image Processing The Scientific World Journal |
| title | A Study of Feature Combination for Vehicle Detection Based on Image Processing |
| title_full | A Study of Feature Combination for Vehicle Detection Based on Image Processing |
| title_fullStr | A Study of Feature Combination for Vehicle Detection Based on Image Processing |
| title_full_unstemmed | A Study of Feature Combination for Vehicle Detection Based on Image Processing |
| title_short | A Study of Feature Combination for Vehicle Detection Based on Image Processing |
| title_sort | study of feature combination for vehicle detection based on image processing |
| url | http://dx.doi.org/10.1155/2014/196251 |
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