Publications and communications of Marc Van Droogenbroeck [u182591]
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See detailViBe: A Disruptive Method for Background Subtraction
Van Droogenbroeck, Marc ULg; Barnich, Olivier

in Bouwans; Porikli; Hoferlin (Eds.) et al Background Modeling and Foreground Detection for Video Surveillance (2014)

This chapter presents ViBe and the underlying ideas of the algorithm. ViBe is an algorithm for the dection of motion by background subtraction. It is a very fast algorithm, based on samples and several ... [more ▼]

This chapter presents ViBe and the underlying ideas of the algorithm. ViBe is an algorithm for the dection of motion by background subtraction. It is a very fast algorithm, based on samples and several innovative processes (time subsampling, random substitution, spatial diffusion, etc). In addtion, we propose a way to measure the computation time by introducing the notion of complexity factor. [less ▲]

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See detailOverview and Benchmarking of Motion Detection Methods
Jodoin, Pierre-Marc; Pierard, Sébastien ULg; Wang, Yi et al

in Bouwmans; Porikli; Hoferlin (Eds.) et al Background Modeling and Foreground Detection for Video Surveillance (2014)

In this chapter, we provide an overview of the most highly cited motion detection meth- ods. We identify the most commonly used background models together with their features, the kind of updating scheme ... [more ▼]

In this chapter, we provide an overview of the most highly cited motion detection meth- ods. We identify the most commonly used background models together with their features, the kind of updating scheme they use, some spatial aggregation models as well as the most widely used post-processing operations. We also provide an overview of datasets used to validate motion detection methods. Please note that this literature review is by no means exhaustive and thus we provide a list of surveys that the reader can rely on for further details. [less ▲]

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See detailOn-the-fly domain adaptation of binary classifiers
Pierard, Sébastien ULg; Marcos Alvarez, Alejandro ULg; Lejeune, Antoine ULg et al

in 23rd Belgian-Dutch Conference on Machine Learning (BENELEARN) (2014, June 06)

This work considers the on-the-fly domain adaptation of supervised binary classifiers, learned off-line, in order to adapt them to a target context. The probability density functions associated to ... [more ▼]

This work considers the on-the-fly domain adaptation of supervised binary classifiers, learned off-line, in order to adapt them to a target context. The probability density functions associated to negative and positive classes are supposed to be mixtures of the source distributions. Moreover, the mixture weights and the priors are only available at runtime. We present a theoretical solution to this problem, and demonstrate the effectiveness of the proposed approach on a real computer vision application. Our theoretical solution is applicable to any classifier approximating Bayes' classifier. [less ▲]

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See detailA New Three Object Triangulation Algorithm for Mobile Robot Positioning
Pierlot, Vincent ULg; Van Droogenbroeck, Marc ULg

in IEEE Transactions on Robotics (2014), 30(3), 566-577

Positioning is a fundamental issue in mobile robot applications. It can be achieved in many ways. Among them, triangulation based on angles measured with the help of beacons is a proven technique. Most of ... [more ▼]

Positioning is a fundamental issue in mobile robot applications. It can be achieved in many ways. Among them, triangulation based on angles measured with the help of beacons is a proven technique. Most of the many triangulation algorithms proposed so far have major limitations. For example, some of them need a particular beacon ordering, have blind spots, or only work within the triangle defined by the three beacons. More reliable methods exist; however, they have an increasing complexity or they require to handle certain spatial arrangements separately. In this paper, we present a simple and new three object triangulation algorithm, named ToTal, that natively works in the whole plane, and for any beacon ordering. We also provide a comprehensive comparison between many algorithms, and show that our algorithm is faster and simpler than comparable algorithms. In addition to its inherent efficiency, our algorithm provides a very useful and unique reliability measure, assessable anywhere in the plane, which can be used to identify pathological cases, or as a validation gate in Kalman filters. [less ▲]

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See detailBeAMS: a Beacon based Angle Measurement Sensor for mobile robot positioning
Pierlot, Vincent ULg; Van Droogenbroeck, Marc ULg

in IEEE Transactions on Robotics (2014), 30(30), 533-549

Positioning is a fundamental issue in mobile robot applications, and it can be achieved in multiple ways. Among these methods, triangulation based on angle measurements is widely used, robust, accurate ... [more ▼]

Positioning is a fundamental issue in mobile robot applications, and it can be achieved in multiple ways. Among these methods, triangulation based on angle measurements is widely used, robust, accurate, and flexible. This paper presents BeAMS, a new active beacon-based angle measurement system used for mobile robot positioning. BeAMS introduces several major innovations. One innovation is the use of a unique unsynchronized channel with On-Off Keying modulated infrared signals to measure angles and to identify the beacons. We also introduce a new mechanism to measure angles: our system detects a beacon when it enters and leaves an angular window. We show that the estimator resulting from the center of this angular window provides an unbiased estimate of the beacon angle. A theoretical framework for a thorough performance analysis of BeAMS is provided. We establish the upper bound of the variance and validate this bound through experiments and simulations; the overall error measure of BeAMS is lower than 0.24 deg for an acquisition rate of 10 Hz. In conclusion, BeAMS is a low power, flexible, and robust solution for angle measurement, and a reliable component for robot positioning. [less ▲]

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See detailDesign of a reliable processing pipeline for the non-intrusive measurement of feet trajectories with lasers
Pierard, Sébastien ULg; Azrour, Samir ULg; Van Droogenbroeck, Marc ULg

in International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (2014, May)

Reliable measurements of feet trajectories are needed in some applications, such as biomedical applications. This paper describes the data processing pipeline used in GAIMS, which is a non-intrusive ... [more ▼]

Reliable measurements of feet trajectories are needed in some applications, such as biomedical applications. This paper describes the data processing pipeline used in GAIMS, which is a non-intrusive system that measures feet trajectories based on multiple range laser scanners. Our processing pipeline relies on a new tracking paradigm, and it is based on two innovative algorithms: the first algorithm localizes the feet directly from the observed point cloud without any clustering, and the other algorithm identifies the feet. After reviewing the various types of noise affecting the point cloud, this paper explains the limitations of the classical processing approach and gives an overview of our new pipeline. The effectiveness of the proposed approach is established by discussing the results that have been obtained in several studies based on GAIMS. [less ▲]

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See detailPerformances of low-level audio classifiers for large-scale music similarity
Osmalsky, Julien ULg; Van Droogenbroeck, Marc ULg; Embrechts, Jean-Jacques ULg

in International Conference on Systems, Signals and Image Processing (2014, May)

This paper proposes a survey of the performances of binary classifiers based on low-level audio features, for music similarity in large-scale databases. Various low-level descriptors are used individually ... [more ▼]

This paper proposes a survey of the performances of binary classifiers based on low-level audio features, for music similarity in large-scale databases. Various low-level descriptors are used individually and then combined using several fusion schemes in a content-based audio retrieval system. We show the performances of the classifiers in terms of pruning and loss and we demonstrate that some combination schemes achieve a better performance at a minimum computational cost. [less ▲]

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See detailMachine learning techniques to assess the performance of a gait analysis system
Pierard, Sébastien ULg; Phan-Ba, Rémy; Van Droogenbroeck, Marc ULg

in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) (2014, April 24)

This paper presents a methodology based on machine learning techniques to assess the performance of a system measuring the trajectories of the lower limbs extremities for the follow-up of patients with ... [more ▼]

This paper presents a methodology based on machine learning techniques to assess the performance of a system measuring the trajectories of the lower limbs extremities for the follow-up of patients with multiple sclerosis. We show how we have established, with the help of machine learning, four important properties about this system: (1) an automated analysis of gait characteristics provides an improved analysis with respect to that of a human expert, (2) after learning, the gait characteristics provided by this system are valuable compared to measures taken by stopwatches, as used in the standardized tests, (3) the motion of the lower limbs extremities contains a lot of useful information about the gait, even if it is only a small part of the body motion, (4) a measurement system combined with a machine learning tool is sensitive to intra-subject modifications of the walking pattern. [less ▲]

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See detailData normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis
Azrour, Samir ULg; Pierard, Sébastien ULg; Geurts, Pierre ULg et al

in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) (2014, April)

Gait impairment is considered as an important feature of disability in multiple sclerosis but its evaluation in the clinical routine remains limited. In this paper, we assess, by means of supervised ... [more ▼]

Gait impairment is considered as an important feature of disability in multiple sclerosis but its evaluation in the clinical routine remains limited. In this paper, we assess, by means of supervised learning, the condition of patients with multiple sclerosis based on their gait descriptors obtained with a gait analysis system. As the morphological characteristics of individuals influence their gait while being in first approximation independent of the disease level, an original strategy of data normalization with respect to these characteristics is described and applied beforehand in order to obtain more reliable predictions. In addition, we explain how we address the problem of missing data which is a common issue in the field of clinical evaluation. Results show that, based on machine learning combined to the proposed data handling techniques, we can predict a score highly correlated with the condition of patients. [less ▲]

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See detailMeasuring feet trajectories: challenges and applications
Pierard, Sébastien ULg; Azrour, Samir ULg; Van Droogenbroeck, Marc ULg

Conference (2013, November 07)

Measuring reliable feet trajectories is needed in many applications. This paper provides the principles used in GAIMS, which is a non-intrusive system that measures feet trajectories based on multiple ... [more ▼]

Measuring reliable feet trajectories is needed in many applications. This paper provides the principles used in GAIMS, which is a non-intrusive system that measures feet trajectories based on multiple range laser scanners. We present the technical challenges that we had to address, as well as an overview of the implemented processing pipeline of GAIMS. [less ▲]

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See detailUsing GAit Measuring System (GAIMS) to discriminate patients with multiple sclerosis from healthy person
Azrour, Samir ULg; Pierard, Sébastien ULg; Van Droogenbroeck, Marc ULg

Poster (2013, November 07)

Among voluntary movements, gait is the most affected by multiple sclerosis. Gait impairment is also a good indicator of the disease progression. However, measurement of gait character- istics made by ... [more ▼]

Among voluntary movements, gait is the most affected by multiple sclerosis. Gait impairment is also a good indicator of the disease progression. However, measurement of gait character- istics made by neurologists is usually limited to the use of a stopwatch. The GAit Measuring System (GAIMS), provides a wider range of measurements that allow the definition of several relevant gait descriptors. The work presented here shows the effectiveness of these gait descriptors and machine learning techniques to discriminate between healthy persons and patients with multiple sclerosis. [less ▲]

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See detailGAIMS: A Reliable Non-Intrusive Gait Measuring System
Pierard, Sébastien ULg; Azrour, Samir ULg; PHAN BA, Remy ULg et al

in ERCIM News (2013), 95

Gait observation and analysis can provide invaluable information about an individual [1]. Studies that have interpreted gait using traditional imaging devices have demonstrated that it is difficult to ... [more ▼]

Gait observation and analysis can provide invaluable information about an individual [1]. Studies that have interpreted gait using traditional imaging devices have demonstrated that it is difficult to make reliable measurements with colour cameras. GAIMS, our new system resulting from a multidisciplinary project born from collaboration between engineers and neurologists, aims at developing non-intrusive and reliable tools to provide quantitative measures of gait and interpretations of the acquired data. Following a current trend in imaging, it takes advantage of imaging sensors that measure distance instead of colour. While its principles are general, GAIMS is currently used for the diagnosis of multiple sclerosis (MS) and the continued evaluation of disease progression [2]. It is the first available system to fully satisfy the clinical routine and its associated constraints. [less ▲]

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See detailRelative Contribution of Walking Speed, Ataxia and Gait asymmetry to the Composition of Gait in Multiple Sclerosis
PHAN BA, Remy ULg; Pierard, Sébastien ULg; LOMMERS, Emilie ULg et al

Poster (2013, October)

Introduction - Objective: Walking speed measured according to the T25FW is the most widely used descriptor of gait in MS clinical research and practice but other dimensions influencing gait variance exist ... [more ▼]

Introduction - Objective: Walking speed measured according to the T25FW is the most widely used descriptor of gait in MS clinical research and practice but other dimensions influencing gait variance exist according to alternative gait analysis methods. The relative importance of these different dimensions of gait relatively to its variance is unknown. Methods: We measured the performances of persons with MS and healthy subjects on the T25FW and the Timed 20-Meter Walk (T20MW) performed in tandem with a new gait analysis system (GAIMS). We performed a factorial analysis of variance to underline the main dimensions influencing gait variance and observed their composition. Findings - Conclusion: The main factor influencing gait variance in conventional walk tests is mostly composed of features related to walking speed. Balance, gait asymmetry and variability also participate to this variance but to a lesser extent. The inverse is observed in tests performed in tandem gait. [less ▲]

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See detailInfluence of the mode of walk on walking speed in multiple sclerosis: are you walking comfortably?
PHAN BA, Remy ULg; DELRUE, Gaël ULg; Pierard, Sébastien ULg et al

Poster (2013, June 10)

Introduction : Walking speed (WS) is the most frequent gait variable taken into account when measuring gait dysfunction in neurological diseases. Influences of the mode of walk instructed to the subject ... [more ▼]

Introduction : Walking speed (WS) is the most frequent gait variable taken into account when measuring gait dysfunction in neurological diseases. Influences of the mode of walk instructed to the subject, i.e. « as fast as possible » (AFAP) or « at a comfortable pace » (PrP) have not been well characterized in multiple sclerosis (MS). Objectives : to compare those 2 mode of walk in a population of persons with MS (pMS) and healthy volunteers (HV). Methods: WS was measured with a new automated device along a 25 foot distance (T25FW) as part of a multimodal evaluation of gait in an MS ambulatory department. Results: Baseline demographics between HV and pMS were comparable. Our first results demonstrate that (i) WS is obviously significantly higher in AFAP than in PrP both for pMS and HV (p < 0.001 for all comparisons) and (ii) the relative difference between AFAP and PrP WS is significantly higher in HV than in pMS (p < 0.001). The AFAP-PrP WS correlation is higher in pMS (r = 0.87, p < 0.001) than in HV (r = 0.51, p < 0.001). Finally, the relative difference between AFAP and PrP WS is significantly and negatively correlated with the PrP WS in HV (r = -0.41, p < 0.001) and pMS with mild to moderate disability (EDSS 0-3.5, r = -0.49, p < 0.01) but not in pMS with high disability (EDSS 4-5.5, r = 0.008). Conclusions : these results suggests that heatlhy subjects have access to a higher range of PrP WS than pMS and questions the regulation of PrP WS that might be under psychological or behavioural influences. The demonstration of a lower PrP-AFAP difference in MS suggests that pMS are either adopting a natural WS closer to their maximum WS, or alternatively that they can’t reach their maximum WS because of neurological impairments. Our results also emphasize the importance of the instructed mode of walk in the quantification of gait disorders both for routine clinical practice and clinical trials. [less ▲]

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See detailStatistical analysis of modulated codes for robot positioning -- Application to BeAMS
Pierlot, Vincent ULg; Van Droogenbroeck, Marc ULg

Report (2013)

Positioning is a fundamental issue for mobile robots. Therefore, a performance analysis is suitable to determine the behavior of a system, and to optimize its working. Unfortunately, some systems are only ... [more ▼]

Positioning is a fundamental issue for mobile robots. Therefore, a performance analysis is suitable to determine the behavior of a system, and to optimize its working. Unfortunately, some systems are only evaluated experimentally, which makes the performance analysis and design decisions very unclear. In [4], we have proposed a new angle measurement system, named BeAMS, that is the key element of an algorithm for mobile robot positioning. BeAMS introduces a new mechanism to measure angles: it detects a beacon when it enters and leaves an angular window. A theoretical framework for a thorough performance analysis of BeAMS has been provided to establish the upper bound of the variance, and to validate this bound through experiments and simulations. It has been shown that the estimator derived from the center of this angular window provides an unbiased estimate of the beacon angle. This document complements our paper by going into further details related to the code statistics of modulated signals in general, with an emphasis on BeAMS. In particular, the probability density function of the measured angle has been previously established with the assumption that there is no correlation between the times a beacon enters the angular window or leaves it. This assumption is questionable and, in this document, we reconsider this assumption and establish the exact probability density function of the angle estimated by BeAMS (without this assumption). The conclusion of this study is that the real variance of the estimator provided by BeAMS was slightly underestimated in our previous work. In addition to this speci c result, we also provide a new and extensive theoretical approach that can be used to analyze the statistics of any angle measurement method with beacons whose signal has been modulated. To summarize, this technical document has four purposes: (1) to establish the exact probability density function of the angle estimator of BeAMS, (2) to calculate a practical upper bound of the variance of this estimator, which is of practical interest for calibration and tracking (see Table 1, on page 13, for a summary), (3) to present a new theoretical approach to evaluate the performance of systems that use modulated (coded) signals, and (4) to show how the variance evolves exactly as a function of the angular window (while re- maining below the upper bound). [less ▲]

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See detailEfficient database pruning for large-scale cover song recognition
Osmalsky, Julien ULg; Pierard, Sébastien ULg; Van Droogenbroeck, Marc ULg et al

in International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (2013, May)

This paper focuses on cover song recognition over a large dataset, potentially containing millions of songs. At this time, the problem of cover song recognition is still challenging and only few methods ... [more ▼]

This paper focuses on cover song recognition over a large dataset, potentially containing millions of songs. At this time, the problem of cover song recognition is still challenging and only few methods have been proposed on large scale databases. We present an efficient method for quickly extracting a small subset from a large database in which a correspondence to an audio query should be found. We make use of fast rejectors based on independent audio features. Our method mixes independent rejectors together to build composite ones. We evaluate our system with the Million Song Dataset and we present composite rejectors offering a good trade-off between the percentage of pruning and the percentage of loss. [less ▲]

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