References of "Pattern Recognition Letters"
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See detailImproving pedestrian detection using motion-guided filtering
Wang, Yi; Pierard, Sébastien ULg; Su, Song-Zhi et al

in Pattern Recognition Letters (in press)

In this letter, we show how a simple motion-guided nonlinear filter can drastically improve the accuracy of several pedestrian detectors. More specifically, we address the problem of how to pre-filter an ... [more ▼]

In this letter, we show how a simple motion-guided nonlinear filter can drastically improve the accuracy of several pedestrian detectors. More specifically, we address the problem of how to pre-filter an image so almost any pedestrian detector will see its false detection rate decrease. First, we roughly identify moving pixels by cumulating their temporal gradient into a motion history image (MHI). The MHI is then used in conjunction with a nonlinear filter to filter out background details while leaving untouched foreground moving objects. We also show how a feedback loop as well as a merging procedure between the filtered and the unfiltered frames can further improve results. We tested our method on 26 videos from 6 categories. The results show that for a given miss rate, filtering out background details reduces the false detection rate by a factor of up to 69.6 times. Our method is simple, computationally light, and can be implemented with any pedestrian detector. Code is made publicly available at: https://bitbucket.org/wany1601/pedestriandetection. [less ▲]

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See detailLaBGen: A method based on motion detection for generating the background of a scene
Laugraud, Benjamin ULg; Pierard, Sébastien ULg; Van Droogenbroeck, Marc ULg

in Pattern Recognition Letters (2016)

Given a video sequence acquired with a fixed camera, the generation of the stationary background of the scene is a challenging problem which aims at computing a reference image for a motionless background ... [more ▼]

Given a video sequence acquired with a fixed camera, the generation of the stationary background of the scene is a challenging problem which aims at computing a reference image for a motionless background. For that purpose, we developed our method named LaBGen, which emerged as the best one during the Scene Background Modeling and Initialization (SBMI) workshop organized in 2015, and the IEEE Scene Background Modeling Contest (SBMC) organized in 2016. LaBGen combines a pixel-wise temporal median filter and a patch selection mechanism based on motion detection. To detect motion, a background subtraction algorithm decides, for each frame, which pixels belong to the background. In this paper, we describe the LaBGen method extensively, evaluate it on the SBI 2016 dataset and compare its performance with other background generation methods. We also study its computational complexity, the performance sensitivity with respect to its parameters, and the stability of the predicted background image over time with respect to the chosen background subtraction algorithm. We provide an open source C++ implementation at http://www.telecom.ulg.ac.be/labgen. [less ▲]

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See detailTowards Generic Image Classification using Tree-based Learning: an Extensive Empirical Study
Marée, Raphaël ULg; Geurts, Pierre ULg; Wehenkel, Louis ULg

in Pattern Recognition Letters (2016)

This paper considers the general problem of image classification without using any prior knowledge about image classes. We study variants of a method based on supervised learning whose common steps are ... [more ▼]

This paper considers the general problem of image classification without using any prior knowledge about image classes. We study variants of a method based on supervised learning whose common steps are the extraction of random subwindows described by raw pixel intensity values and the use of ensemble of extremely randomized trees to directly classify images or to learn image features. The influence of method parameters and variants is thoroughly evaluated so as to provide baselines and guidelines for future studies. Detailed results are provided on 80 publicly available datasets that depict very diverse types of images (more than 3800 image classes and over 1.5 million images). [less ▲]

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See detailA sorting optimization curve with quality and yield requirements
Ooms, David ULg; Palm, Rodolphe ULg; Leemans, Vincent ULg et al

in Pattern Recognition Letters (2010), 31(9), 983-990

Binary classifiers used for sorting can be compared and optimized using receiver-operating characteristic (ROC) curves which describe the trade-off between the false positive rate and true positive rate ... [more ▼]

Binary classifiers used for sorting can be compared and optimized using receiver-operating characteristic (ROC) curves which describe the trade-off between the false positive rate and true positive rate of the classifiers. This approach is well suited for the diagnosis of human diseases where individual costs of misclassification are of great concern. While it can be applied to the sorting of merchandise or other materials, the variables described by the ROC curve and its existing alternatives are less relevant for that range of applications and another approach is needed. In this paper, quality and yield factors are introduced into a sorting optimization curve (SOC) for the choice of the operating point of the classifier, associated with the prediction of output quantity and quality. Given examples are the sorting of seeds and apples with specific requirements. In both cases the operating point of the classifier is easily chosen on the SOC, while the output characteristics of the sorted product are accurately predicted. [less ▲]

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See detailFrontal-view gait recognition by intra- and inter-frame rectangle size distribution
Barnich, Olivier ULg; Van Droogenbroeck, Marc ULg

in Pattern Recognition Letters (2009), 30

Current trends seem to accredit gait as a sensible biometric feature for human identification, at least in a multimodal system. In addition to being a robust feature, gait is hard to fake and requires no ... [more ▼]

Current trends seem to accredit gait as a sensible biometric feature for human identification, at least in a multimodal system. In addition to being a robust feature, gait is hard to fake and requires no cooperation from the user. As in many video systems, the recognition confidence relies on the angle of view of the camera and on the illumination conditions, inducing a sensitivity to operational conditions that one may wish to lower. In this paper we present an efficient approach capable of recognizing people in frontal-view video sequences. The approach uses an intra-frame description of silhouettes which consists of a set of rectangles that will fit into any closed silhouette. A dynamic, inter-frame, dimension is then added by aggregating the size distributions of these rectangles over multiple successive frames. For each new frame, the inter-frame gait signature is updated and used to estimate the identity of the person detected in the scene. Finally, in order to smooth the decision on the identity, a majority vote is applied to previous results. In the final part of this article, we provide experimental results and discuss the accuracy of the classification for our own database of 21 known persons, and for a public database of 25 persons. [less ▲]

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See detailFast Computation of morphological operations with arbitrary structuring elements
Van Droogenbroeck, Marc ULg; Talbot, Hugues

in Pattern Recognition Letters (1996), 17(14), 1451-1460

Detailed reference viewed: 62 (6 ULg)