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This paper describes a new system for detecting pedestrians using the rear-view camera only. The system is based on "Accelerated Feature Synthesis" (AFS) part-based object detection which enables the detection of pedestrians across a wide range of appearance changes: upright and non-upright pedestrians, partially occluded pedestrians and children. In this paper we enhance the AFS by introducing...
We present a new vision-based pedestrian detection system for rear-view cameras which is robust to partial occlusions and non-upright poses. Detection is made using a single automotive rear-view fisheye lens camera. The system uses “Accelerated Feature Synthesis”, a multiple-part based detection method with state-of-the-art performance. In addition, we collected and annotated an extensive dataset...
In this work we present a new part-based object detection algorithm with hundreds of parts performing real-time detection. Part-based models are currently state-of-the-art for object detection due to their ability to represent large appearance variations. However, due to their high computational demands such methods are limited to several parts only and are too slow for practical real-time implementation...
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