Pedestrian detection is a classical and hot issue in object detection. Many approaches have been proposed in this area. However, it remains a challenging problem due to the variances in lighting conditions, scene structures, clothes, view angles, postures, scales, occlusions, etc. Previous survey [1] has summarized that using better features plays an important role in improving detection qualit...

A novel method for creating diverse ensembles of image classifiers is proposed. The idea is that, for each base image classifier in the ensemble, a random image transformation is generated and applied to all of the images in the labeled training set. The base classifiers are then learned using features extracted from these randomly transformed versions of the training data, and the result is a ...

Pedestrian detection in real world scenes is a challenging problem. In recent years a variety of approaches have been proposed, and impressive results have been reported on a variety of databases. This paper systematically evaluates (1) various local shape descriptors, namely Shape Context and Local Chamfer descriptor and (2) four different interest point detectors for the detection of pedestri...

09:30-09:50 Robust Background-Subtraction for Person Detection in Thermal Imagery, James W. Davis and Vinay Sharma, Ohio State U, Columbus, OH, USA 09:50-10:10 Motion Detection Based on Local Variation of Spatiotemporal Texture, Longin Jan Latecki, Roland Miezianko, Dragoljub Pokrajac, Temple University, Philadelphia, and Delaware State University, Dover, DE, USA 10:10-10:30 Pedestrian Detectio...

In recent years, demand for pedestrian detection using inexpensive low-resolution LIDAR (LIght Detection And Ranging) is increasing, as it can be used to prevent traffic accidents involving pedestrians. However, it is difficult to detect pedestrians from a low-resolution (sparse) point-cloud obtained by a low-resolution LIDAR. In this paper, we propose multi-frame features calculated by integra...

This paper investigates the robustness of a new thermal-infrared pedestrian detection system under different outdoor environmental conditions. In first place the algorithm for pedestrian ROI extraction in thermal-infrared video based on both thermal and motion information is introduced. Then, the evaluation of the proposal is detailed after describing the complete thermal and motion information...

In this paper, we propose a simple nonlinear filter which improves the detection of pedestrians walking in a video. We do so by first cumulating temporal gradient of moving objects into a motion history image (MHI). Then we apply to each frame of the video a motion-guided nonlinear filter whose goal is to smudge out background details while leaving untouched foreground moving objects. The resul...

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 basically use Co-occurrence Histograms of Oriented Gradients (CoHOG) as a feature descriptor. While the CoHOG feature provides high classification perfo...

This article presents a stereo system for the detection of pedestrians using far-infrared cameras. Since pedestrian detection in far-infrared images can be difficult in some environmental conditions, the system exploits three different detection approaches: warm area detection, edge-based detection, and disparity computation. A final validation process is performed using head morphological and ...

Cascades help make sliding window object detection fast, nevertheless, computational demands remain prohibitive for numerous applications. Currently, evaluation of adjacent windows proceeds independently; this is suboptimal as detector responses at nearby locations and scales are correlated. We propose to exploit these correlations by tightly coupling detector evaluation of nearby windows. We i...