Fast multi-feature pedestrian detection algorithm based on histogram of oriented gradient using discrete wavelet transform
A convergence between a natural user interface (NUI) and advanced driver assistance system is considered as a next generation technology. This kind of interfacing system technology becomes more popular in driver assistance system of automobile. Especially, pedestrian detection is an important cue fo...
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| Veröffentlicht in: | Multimedia tools and applications 2016-12, Vol.75 (23), p.15229-15245 |
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| container_title | Multimedia tools and applications |
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| creator | Hong, Gwang-Soo Kim, Byung-Gyu Hwang, Young-Sup Kwon, Kee-Koo |
| description | A convergence between a natural user interface (NUI) and advanced driver assistance system is considered as a next generation technology. This kind of interfacing system technology becomes more popular in driver assistance system of automobile. Especially, pedestrian detection is an important cue for intelligent vehicles and interactive driver assistance system. In this paper, we propose a pedestrian detection feature and technique by combining histogram of the oriented gradient (HOG) and discrete wavelet transform (DWT). In the method, the magnitude of motion is used to set region of interest (ROI) for improving detection speed. Then, we employ multi-feature for a pedestrian detection based on the HOG and DWT. In last stage, to classify whether a candidate window contains a pedestrian or not, the designed multi-feature is learned by using the training data with the support vector machine (SVM) mechanism. Experimental results show that the proposed algorithm increases the speed-up factor of 27.21 % by comparing to the existing method using the original HOG feature. |
| doi_str_mv | 10.1007/s11042-015-2455-2 |
| format | Article |
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This kind of interfacing system technology becomes more popular in driver assistance system of automobile. Especially, pedestrian detection is an important cue for intelligent vehicles and interactive driver assistance system. In this paper, we propose a pedestrian detection feature and technique by combining histogram of the oriented gradient (HOG) and discrete wavelet transform (DWT). In the method, the magnitude of motion is used to set region of interest (ROI) for improving detection speed. Then, we employ multi-feature for a pedestrian detection based on the HOG and DWT. In last stage, to classify whether a candidate window contains a pedestrian or not, the designed multi-feature is learned by using the training data with the support vector machine (SVM) mechanism. 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This kind of interfacing system technology becomes more popular in driver assistance system of automobile. Especially, pedestrian detection is an important cue for intelligent vehicles and interactive driver assistance system. In this paper, we propose a pedestrian detection feature and technique by combining histogram of the oriented gradient (HOG) and discrete wavelet transform (DWT). In the method, the magnitude of motion is used to set region of interest (ROI) for improving detection speed. Then, we employ multi-feature for a pedestrian detection based on the HOG and DWT. In last stage, to classify whether a candidate window contains a pedestrian or not, the designed multi-feature is learned by using the training data with the support vector machine (SVM) mechanism. Experimental results show that the proposed algorithm increases the speed-up factor of 27.21 % by comparing to the existing method using the original HOG feature.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11042-015-2455-2</doi><tpages>17</tpages></addata></record> |
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| subjects | Accident prevention Algorithms Analysis Autonomous vehicles Candidates Computer Communication Networks Computer Science Convergence Data Structures and Information Theory Discrete Wavelet Transform Drivers Histograms Hypotheses Intelligent vehicles Multimedia Information Systems Pedestrians Special Purpose and Application-Based Systems Studies Support vector machines User interface Vision systems Wavelet transforms |
| title | Fast multi-feature pedestrian detection algorithm based on histogram of oriented gradient using discrete wavelet transform |
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