کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
532063 | 869903 | 2014 | 10 صفحه PDF | دانلود رایگان |
• The proposed PPMPF is utilized to initially filter out most of the non-pedestrian regions.
• Independent orientation and magnitude features are adopted as descriptors for pedestrians.
• A superior performance can be achieved compared to the former HOG and the edgelet.
The pedestrian detection is a popular research field in recent years, yet the low-resolution issue is rarely discussed for yielding detection accuracy for drivers. In this study, a hierarchical pedestrian detection system is proposed to cope with this issue. In which, two independent features, orientation and magnitude, are adopted as descriptors for pedestrians. Moreover, the proposed probability-based pedestrian mask pre-filtering (PPMPF) is utilized to initially filter out non-pedestrian regions meanwhile retaining most of the real pedestrians. In experimental results, the use of the two proposed features can provide superior performance than the former well-known histogram of oriented gradient (HOG; high accuracy) and the edgelet (high processing efficiency) simultaneously without carrying their lacks. Moreover, the PPMPF can also boost the processing efficiency by a factor of around 2.82 in contrast to the system without this pre-filtering strategy. Thus, the proposed method can be a very competitive candidate for intelligent surveillance applications.
Journal: Pattern Recognition - Volume 47, Issue 4, April 2014, Pages 1616–1625