We describe a real-time pedestrian detection system intended for use in automotive applications. Our system demonstrates superior detection performance when compared to many state-of-the-art detectors and is able to run at a speed of 14 fps on an Intel Core i7 computer when applied to 640×480 images. Our approach uses an analysis of geometric constraints to efficiently search feature pyramids a...

Pedestrian detection has been an active area of research in recent years; its interest relies on the potential positive impact on quality of life of the related applications (surveillance systems, automotive safety, robotics, multimedia content analysis, assistive technology and advanced interactive interfaces, among others). The large variability of human appearances, poses and context conditi...

The demand for pedestrian detection and tracking algorithms is rapidly increasing with applications in security systems, human computer interaction and human activity analysis. A pedestrian is a person standing in an upright position. Previous work involves using various types of image descriptors to detect humans. However, the existing approaches, although exhibit low misdetection rate, result...

This paper describes how multisensor data fusion increases reliability of pedestrian detection while using a Bayesian combination of features. The clue is to combine in a probabilistic framework, the detecting capabilities of sensors for identifying pedestrians located along the vehicle trajectory. The work emphasizes the idea of redundancy due to the different nature of the information provide...

In the last 3 decades, between 4378 (in 2008) and 8090 (in 1979) pedestrians were killed each year in motor vehicle related crashes, representing 11% to 17% of the total roadway fatalities. Although the numbers of pedestrian deaths have been in decline steadily since 1980, their distributions have become more and more concentrated in urban areas. There is an urgent need to develop reliable pede...

Reliable and fast pedestrian detection in mobile systems is an important and increasing field of research. The main goal is to save lives of pedestrians in as many situations and environments as possible. Most of the existing reliable pedestrian detection algorithms run on high performance PCs with intense CPU and GPU usage and are therefore not suited for mobile embedded systems. We present a ...

Pedestrian detection in still image should handle the large appearance and stance variations arising from the articulated structure, various clothing of human as well as viewpoints. In this paper, we address this problem from a view which utilizes multiple instances to represent the variations in multiple instance learning (MIL) framework. Specifically, logistic multiple instance boost (LMIBoos...

Multispectral images of color-thermal pairs have shown more effective than a single color channel for pedestrian detection, especially under challenging illumination conditions. However, there is still a lack of studies on how to fuse the two modalities effectively. In this paper, we deeply compare six different convolutional network fusion architectures and analyse their adaptations, enabling ...

Pedestrian safety continues to be a significant concern in urban communities and pedestrian distraction is emerging as one of the main causes of grave and fatal accidents involving pedestrians. The advent of sophisticated mobile and wearable devices, equipped with high-precision on-board sensors capable of measuring fine-grained user movements and context, provides a tremendous opportunity for ...

This work explores three schemes for pedestrian detection in urban scenarios using information gathered by a LIDAR and a monocular camera mounted on an electric vehicle. In the first scheme, pedestrian detection is conduct by a set of single classification methods trained with LIDAR and/or vision-based features. In the second scheme, the likelihoods from the single-classifiers are fused by mean...