Luis Salgado

Universidad Politécnica de Madrid | UPM · Departamento de Señales, Sistemas y Radiocomunicaciones

Tremendous advances in advanced driver assistance systems (ADAS) have been possible thanks to the emergence of deep neural networks (DNN) and Big Data (BD) technologies. Huge volumes of data can be managed and consumed as training material to create DNN models which feed functions such as lane keeping systems (LKS), automated emergency braking (AEB...

Driver Monitoring Systems (DMS) operate by measuring the state of the driver while performing driving activities. At the gates of the arrival of SAE-L3 autonomous driving vehicles, DMS are called to play a major role for guarantee or, at least, support safer mode transfer transitions (between manual and automated driving modes). Drowsiness and fati...

Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of sufficiently large and comprehensive datasets is currently a bottleneck for the progress of DMS development, crucial for the transition of automated driving from SAE Level-2 to...

Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of sufficiently large and comprehensive datasets is currently a bottleneck for the progress of DMS development, crucial for the transition of automated driving from SAE Level-2 to...

This work presents the “Blexer” (Blender Exergames) system for therapeutic exergames designed for people with physical dysfunctionalities. The users control the games with corporal movements, captured by the Kinect® sensor. Games incorporate an amplifying functionality that enhances the immersive feeling. Via the medical platform “Blexer-med”, clin...

This paper presents an objective comparison between two approaches for anomaly detection in surveillance scenarios. Gaussian mixture models (GMM) are used in both cases: globally, with a unique model that covers the whole scene; and locally, with one model per spatial location. The two approaches follow a “bottom-up” approach that avoids any object...

In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in...

The problem of dust resuspension in case of Loss Of Vacuum Accident (LOVA) in a nuclear fusion plant (ITER or DEMO like) is an important issue for the safety of workers and the security of environment. The Quantum Electronics and Plasma Physics Research Group has implemented an optical set-up to track dust during a LOVA reproduction inside the expe...

Histograms of Oriented Gradients (HoGs) provide excellent results in object detection and verification. However, their demanding processing requirements bound their applicability in some critical real-time scenarios, such as for video-based on-board vehicle detection systems. In this work, an efficient HOG configuration for pose-based on-board vehi...

In the recent years, the computer vision community has shown great interest on depth-based applications thanks to the performance and flexibility of the new generation of RGB-D imagery. In this paper, we present an efficient background subtraction algorithm based on the fusion of multiple region-based classifiers that processes depth and color data...

Vision-based object detection from a moving platform becomes particularly challenging in the field of advanced driver assistance systems (ADAS). In this context, onboard vision-based vehicle verification strategies become critical, facing challenges derived from the variability of vehicles appearance, illumination, and vehicle speed. In this paper,...

According to United Nations, more than half of the population of the Earth now lives in urban areas. The need to rethink the city in efficient and modern ways, including new actors in the scene such as automatic decision makers, has motivated plenty of national and international initiatives to foster ICT research and innovation in this field. For t...

This work addresses the use of image analysis and computer vision in the context of Advance Driver Assistance Systems (ADAS). Video-based systems stand as a powerful complement to classical active-sensor based approaches, as their being non-intrusive avoids interferences between sensors. They also allow a deeper understanding of the scene and offer...

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use o...

Low-cost systems that can obtain a high-quality foreground segmentation almostindependently of the existing illumination conditions for indoor environments are verydesirable, especially for security and surveillance applications. In this paper, a novelforeground segmentation algorithm that uses only a Kinect depth sensor is proposedto satisfy the a...

Low cost RGB-D cameras such as the Microsoft’s Kinect or the Asus’s Xtion Pro are completely changing the computer vision world, as they are being successfully used in several applications and research areas. Depth data are particularly attractive and suitable for applications based on moving objects detection through foreground/background segmenta...

An innovative background modeling technique that is able to accurately segment foreground regions in RGB-D imagery (RGB plus depth) has been presented in this paper. The technique is based on a Bayesian framework that efficiently fuses different sources of information to segment the foreground. In particular, the final segmentation is obtained by c...

Image-based vehicle detection has received increasing attention in recent years in the framework of advanced driver assistance systems. However, the variability of vehicles in size, color, shape, etc. poses an enormous challenge, especially for the vehicle verification task. Histograms of Oriented Gradients (HOGs) have successfully been applied to...

In this paper we present an efficient system for real-time RGB-D camera data processing on GPU architecture. Its goal is to improve the depth data accuracy while processing the RGB-D data stream in real time, thus being very attractive for depth-based interactive applications such as gesture recognition for human-computer interaction, 3D scene mode...

Vehicle detection based on image analysis has attracted increasing attention in recent years due to its low cost, flexibility and potential towards collision avoidance. In particular, vehicle verification is especially challenging on account of the heterogeneity of vehicles in color, size, pose, etc. Imagebased vehicle verification is usually addre...

A novel approach to real-time lane modeling using a single camera is proposed. The proposed method is based on an efficient design and implementation of a particle filter which applies the concepts of the Rao-Blackwellized particle filter (RBPF) by separating the state into linear and non-linear parts. As a result the dimensionality of the problem...

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments....

In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The m...

In this paper, we present a depth-color scene modeling strategy for indoors 3D contents generation. It combines depth and visual information provided by a low-cost active depth camera to improve the accuracy of the acquired depth maps considering the different dynamic nature of the scene elements. Accurate depth and color models of the scene backgr...

Video-based vehicle detection is the focus of increasing interest due to its potential towards collision avoidance. In particular, vehicle verification is especially challenging due to the enormous variability of vehicles in size, color, pose, etc. In this paper, a new approach based on supervised learning using Principal Component Analysis (PCA) i...

In this paper we present an innovative technique to tackle the problem of automatic road sign detection and tracking using an on-board stereo camera. It involves a continuous 3D analysis of the road sign during the whole tracking process. Firstly, a color and appearance based model is applied to generate road sign candidates in both stereo images....

This paper presents a strategy for solving the feature matching problem in calibrated very wide-baseline camera settings. In this kind of settings, perspective distortion, depth discontinuities and occlusion represent enormous challenges. The proposed strategy addresses them by using geometrical information, specifically by exploiting epipolarconst...

One of the main challenges for intelligent vehicles is the capability of detecting other vehicles in their environment, which constitute the main source of accidents. Specifically, many methods have been proposed in the literature for video-based vehicle detection. Most of them perform supervised classification using some appearance-related feature...

In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is ge...

We propose a new method to automatically refine a facial disparity map obtained with standard cameras and under conventional illumination conditions by using a smart combination of traditional computer vision and 3D graphics techniques. Our system inputs two stereo images acquired with standard (calibrated) cameras and uses dense disparity estimati...

In this paper we present an efficient hole filling strategy that improves the quality of the depth maps obtained with the Microsoft Kinect device. The proposed approach is based on a joint-bilateral filtering framework that includes spatial and temporal information. The missing depth values are obtained applying iteratively a joint-bilateral filter...

In this paper we propose an innovative method for the automatic detection and tracking of road traffic signs using an onboard stereo camera. It involves a combination of monocular and stereo analysis strategies to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. Firstly, an ad...

In this paper we present an adaptive spatio-temporal filter that aims to improve low-cost depth camera accuracy and stability over time. The proposed system is composed by three blocks that are used to build a reliable depth map of static scenes. An adaptive joint-bilateral filter is used to obtain consistent depth maps by jointly considering depth...

In this paper we present a low-cost efficient Interactive Whiteboard that, by fusing depth and video information provided by a low-cost depth camera, is able to detect and track user movements.

We present an adaptive and efficient background modeling strategy for real-time object detection in multicamera systems. The proposed approach is an innovative multiparameter adaptation strategy of the mixture of Gaussian (MoG) background modeling algorithm. This approach is able to efficiently adjust the computational requirements of the tasks to...

Recently, vision-based advanced driver-assistance systems (ADAS) have received a new increased interest to enhance driving safety. In particular, due to its high performance–cost ratio, mono-camera systems are arising as the main focus of this field of work. In this paper we present a novel on-board road modeling and vehicle detection system, which...

This paper introduces a new method for the simultaneous computation of sets of lines meeting at multiple vanishing points through the use of the Expectation–Maximisation (EM) algorithm. The proposed method is based on the formulation of novel error functions in the projective plane between lines and points which involve the use of non-linear optimi...

In this paper we propose a new method for the automatic detection and tracking of road traffic signs using an on-board single camera. This method aims to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. The proposed approach exploits a combination of different features, such a...

A new line segment detection approach is introduced in this paper for its application in real-time computer vision systems. It has been designed to work unsupervised without any prior knowledge of the imaged scene; hence, it does not require tuning of input parameters. Although many works have been presented on this topic, as far as we know, none o...

In the field of detection and monitoring of dynamic objects in quasi-static scenes, background subtraction techniques where background is modeled at pixel-level, although showing very significant limitations, are extensively used. In this work we propose a novel approach to background modeling that operates at region-level in a wavelet based multi-...

In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running...

In this paper we present an adaptive multi-camera system for real time object detection able to efficiently adjust the computational requirements of video processing blocks to the available processing power and the activity of the scene. The system is based on a two level adaptation strategy that works at local and at global level. Object detection...

Object tracking through particle filtering has been widely addressed in recent years. However, most works assume a constant number of objects or utilize an external detector that monitors the entry or exit of objects in the scene. In this work, a novel tracking method based on particle filtering that is able to automatically track a variable number...

This paper introduces a new strategy for plane rectification in sequences of images, based on the Expectation-Maximization (EM) algorithm. Our approach is able to compute simultaneously the parameters of the dominant vanishing point in the image plane and the most significant lines passing through it. It is based on a novel definition of the likeli...

A new method for robust estimation of vanishing points is introduced in this paper. It is based on the MSAC (M-estimator Sample and Consensus) algorithm and on the definition of a new distance function between a vanishing point and a given orientation. Apart from the robustness, our method represents a flexible and efficient solution, since it allo...

This paper presents an innovative procedure, capable to automatically generate virtual environments which are applicable to art galleries, museums or similar facilities, and suitable for web-based promotions of artists and their works. The presented system is part of the outcome of an interdisciplinary research for low-cost and platform independent...

This study presents a robust method for ground plane detection in vision-based systems with a non-stationary camera. The proposed method is based on the reliable estimation of the homography between ground planes in successive images. This homography is computed using a feature matching approach, which in contrast to classical approaches to on-boar...

This paper presents a full system for vehicle detection and tracking in non-stationary settings based on computer vision. The method proposed for vehicle detection exploits the geometrical relations between the elements in the scene so that moving objects (i.e., vehicles) can be detected by analyzing motion parallax. Namely, the homography of the r...

Vanishing points are elements of great interest in the computer vision field, since they are the main source of information about the geometry of the scene and the projection process associated to the camera. They have been studied and applied during decades for plane rectification, 3D reconstruction, and mainly auto-calibration tasks. Nevertheless...

Multiple object tracking is a main research area in the computer vision field. Particle filters have shown their performance as a powerful tool allowing to track visual objects giving temporal coherence to incoming observations, as well as offering an excellent framework for this task due to its inherent multimodality. However, traditional algorith...

Visual tracking with moving cameras is a challenging task. The global motion induced by the moving camera moves the target object outside the expected search area, according to the object dynamics. The typical approach is to use a registration algorithm to compensate the camera motion. However, in situations involving several moving objects, and ba...

Automatic target tracking in airborne FLIR imagery is currently a challenge due to the camera ego-motion. This phenomenon distorts the spatio-temporal correlation of the video sequence, which dramatically reduces the tracking performance. Several works address this problem using ego-motion compensation strategies. They use a deterministic approach...

In recent years advanced driver assistance systems (ADAS) have received increasing interest to confront car accidents. In particular, video processing based vehicle detection methods are emerging as an efficient way to address accident prevention. Many video-based approaches are proposed in the literature for vehicle detection, involving sophistica...

Video synchronization is one of the first steps in most of the multi-camera systems. In this paper we introduce a novel, computationally simple and reliable approach for video synchronization that does not require any pre-computed camera geometries or tracking certain features. We define a feature called center of motion (COM) and obtain its trajec...

Road modeling is the first step towards environment perception within driver assistance video-based systems. Typically, lane modeling allows applications such as lane departure warning or lane invasion by other vehicles. In this paper, a new monocular image processing strategy that achieves a robust multiple lane model is proposed. The identificati...

People positioning and tracking in 3D indoor environments are challenging tasks due to background clutter and occlusions. Current works are focused on solving people occlusions in low-cluttered backgrounds, but fail in high-cluttered scenarios, specially when foreground objects occlude people. In this paper, a novel 3D people positioning and tracki...

Visual surveillance and monitoring of indoor environments using multiple cameras has become a field of great activity in computer vision. Usual 3D tracking and positioning systems rely on several independent 2D tracking modules applied over individual camera streams, fused using geometrical relationships across cameras. As 2D tracking systems suffe...

Video sequences acquired by a camera mounted on a hand held device or a mobile platform are affected by unwanted shakes and jitters. In this situation, the performance of video applications, such us motion segmentation and tracking, might dramatically be decreased. Several digital video stabilization approaches have been proposed to overcome this p...

Most multi-camera 3D tracking and positioning systems rely on several independent 2D tracking modules applied over individual camera streams, fused using both geometrical relationships across cameras and/or observed appearance of objects. However, 2D tracking systems suffer inherent difficulties due to point of view limitations (perceptually simila...

In this paper, a novel road modeling strategy is proposed, defining an accurate and robust system that operates in real-time. The strategy aims to find a trade-off between computational requirements of real systems and accuracy and robustness of the results. The basis of the strategy is an adaptive road segmentation technique which ensures robust d...

Driver assistance systems based on video processing deliver a number of warnings to the driver, such as lane departure, lane invasion by other vehicles, collision prediction, etc. This have been a field of intense research for many years, providing solutions based on road models where vehicles are afterwards detected and tracked. Robustness is esse...

In this paper a new fast mode decision (FMD) algorithm is proposed for the recent H.264/AVC video coding standard, aiming to reduce its computational load without loosing coding efficiency. This algorithm identifies redundancy and selects the minimum sub-set of modes for each macroblock (MB) required to provide high rate-distortion (RD) efficiency....

Motion estimation in video sequences is a classical intensive computational task that is required for a wide range of applications. Many different methods have been proposed to reduce the computational complexity, but the achieved reduction is not enough to allow real time operation in a non-specialized hardware. In this paper an efficient selectio...

Here, a new and efficient strategy is introduced which allows moving objects detection and segmentation in video sequences. Other strategies use the mixture of gaussians to detect static areas and dynamic areas within the images so that moving objects are segmented [1], [2], [3], [4]. For this purpose, all these strategies use a fixed number of gau...

Video-based Driver Assitance Systems (ADAS) are a promising and chellenging field of work within the Intelligent Transportation System framework. Thwe Grupo Tratamiento de Imágenes is a research group that has an structured view of vision-vased applications, including video-based ADAS. The most important project in which the group is envolved regar...

This paper presents a robust method for real-time vehicle detection and tracking in dynamic traffic environments. The proposed strategy aims to find a trade-off between the robustness shown by time-uncorrelated detection techniques and the speed-up obtained with tracking algorithms. It combines both advantages by continuously evaluating the quality...

An efficient automatic detection strategy for aerial moving targets in airborne forward-looking infrared (FLIR) imagery is presented in this paper. Airborne cameras induce a global motion over all objects in the image, that invalidates motion-based segmentation techniques for static cameras. To overcome this drawback, previous works compensate the...

This paper presents an innovative road modeling strategy for video-based driver assistance systems. It is based on the real-time estimation of the vanishing point of sequences captured with forward looking cameras located near the rear view mirror of a vehicle. The vanishing point is used for many purposes in video-based driver assistance systems,...

Fatalities and injuries connected with road accidents and its social and economic implications are dramatic issues nowadays. In this paper we present a strategy to improve road and mobility safety addressed by the I-WAY system. I-WAY is an innovative system able to improve road safety based on a cooperative driving platform which will ubiquitously...

In this work, a new inverse perspective mapping (IPM) technique is proposed based on a robust estimation of the vanishing point, which provide bird-view images of the road, so that facilitating the tasks of road modeling and vehicle detection and tracking. This new approach has been design to cope with the instability that cameras mounted on a movi...

Common strategies for detection and tracking of aerial moving targets in airborne Forward-Looking Infrared (FLIR) images offer accurate results in images composed by a non-textured sky. However, when cloud and earth regions appear in the image sequence, those strategies result in an over-detection that increases very significantly the false alarm r...