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High accuracy pedestrian detection plays an important role in all intelligent vehicles. This paper describes a system for detecting the obstacles in front of the vehicle and classifying them in pedestrians and non-pedestrians. It acquires the traffic scenes using a low-cost pair of gray intensities stereo cameras. A SORT-SGM stereo-reconstruction technique is used in order to obtain high density and...
To improve automotive active safety and guarantee the safety of pedestrians at night time, a fast pedestrian detection method based on monocular far-infrared camera for driver assistance systems is proposed. According to the distribution of gray-level intensity of pedestrian samples, an adaptive local dual threshold segmentation algorithm is executed first to extract candidate regions. The presented...
In this paper, we focus on a challenging pattern recognition problem of significant industrial impact: classifying vehicles from their rear videos as observed by a camera mounted on top of a highway with vehicles traveling at high speed. To solve this problem, we present a novel feature called structural signatures. From a rear view video, a structural signature recovers the vehicle side profile information...
In this paper we describe and evaluate two methods underpinning a surveillance-based content management system, designed for monitoring and profiling freight-based vehicular traffic in a seaport environment. The ‘InSPeCT’ system captures video footage of passing vehicles, and uses tailored optical character recognition (OCR) to index the footage according to vehicle license-plates and freight codes...
One of the core components of any visual surveillance system is object classification, where detected objects are classified into different categories of interest. Although in airports or train stations, abandoned objects are mainly luggage or trolleys, none of the existing works in the literature have attempted to classify or recognize trolleys. In this paper, we analyzed and classified images of...
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