http://dx.doi.org/10.1016/j.eswa.2014.04.034 0957-4174/ 2014 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. Tel.: +34 6248325; fax: +34 916249430. E-mail addresses: [email protected] (F. García), [email protected] (J. García), [email protected] (A. Ponz), [email protected] (A. de la Escalera), [email protected] (J.M. Armingol). Fernando García a,⇑, Jesús García , Aurelio P...

In this paper, we address the challenging task of pedestrian detection. The topic keyword Real-World should be noted as a synonym for a realistic detection environment (e.g. real-time, robustness, occlusions). We present some basic approaches for urban human detection and refine them to a suitable solution. We then discuss problems of detectors with common scene conditions and introduce an dete...

In order to offer more security and safety for pedestrians and drivers at night, it is becoming more and more important to extend a driver's night vision capability, especially for older drivers or drivers with visual limitations. For this purpose, several night vision systems have been developed relying on infrared cameras, which detect heat from objects and are calibrated to be sensitive to t...

This paper presents a system for pedestrian detection and tracking by using image processing techniques. A very important issue in the field of intelligent transportation system is to prevent pedestrians from being hit by vehicles. Recently, a great number of vision-based techniques have been proposed for this purpose. In this paper, we propose a vision-based method which combines the use of a ...

Domain adaptation addresses learning tasks where training is performed on data from one domain whereas testing is performed on data belonging to a different but related domain. Assumptions about the relationship between the source and target domains should lead to tractable solutions on the one hand, and be realistic on the other hand. Here we propose a generative domain adaptation model that a...

The training and the evaluation of learning algorithms depend critically on the quality of data samples. We denote as pure the samples that identify clearly and without any ambiguity the class of objects of interest. For instance, in pedestrian detection algorithms, we consider as pure samples the ones containing persons who are fully visible and are imaged at a good resolution (larger than the...

Detecting pedestrians from a moving vehicle is a challenging problem since the essence of the task is to search non-rigid moving objects with various appearances in a dynamic and outdoor environment. In order to alleviate these difficulties, we propose a new human detection framework which makes the most use of stereo vision. While the conventional stereo-based detection methods initially gener...

Visual surveillance data might encompass vast data amounts. Given the amount of data the need for search and data exploration arises naturally. Various authorities such as infrastructure operators and law enforcement agencies are confronted with search needs based on a visual description and/or behavioral patterns (motion path, activity) in order to find a ”needle in a haystack of digital data”...

Notation Vectors are denoted by lower-case bold letters, e.g., x, matrices are denoted by upper-case bold letters, e.g., X and sets are denoted by calligraphic upper-case letters, e.g., X. All vectors are assumed to be column vectors. The (i, j) entry of X is xij . Let {x+i }i=1 be a set of pedestrian training examples and {xj }j=1 be a set of non-pedestrian training examples. The tuple of all ...

Pedestrian detection is an important problem in computer vision due to its importance for applications such as visual surveillance, robotics, and automotive safety. This paper pushes the state-of-the-art of pedestrian detection in two ways. First, we propose a simple yet highly effective novel feature based on binocular disparity, outperforming previously proposed stereo features. Second, we sh...