ABSTRACT This paper presents the architecture of a system to provide user orientation with the ca... more ABSTRACT This paper presents the architecture of a system to provide user orientation with the capability to automatically show multimedia information (audio, static images, panoramic images, VRML models, HTML pages) according to the user real or virtual location within a ...
In spite of their advantages, region-based approaches present a heavy burden in the required amou... more In spite of their advantages, region-based approaches present a heavy burden in the required amount of information to describe region contours. To avoid these limitations, a new region-based motion estimation and compensation strategy is proposed, which allows the operation on arbitrary shaped regions and the ability to reconstruct them without any contour information. The strategy is enhanced by the use of multivector motion estimation and compensation. Results showing the quality and advantages of the strategy are provided
A new method for the determination of adaptive palettes of color images with a variation of Kohon... more A new method for the determination of adaptive palettes of color images with a variation of Kohonen (1984) networks, for the purposes of image storage and display, is presented. New neighborhood relationships in one and three dimensions are defined among neurons and the scope of these binds is also extended. The presented method is compared with popular palette selection algorithms, the resulting quality, provided network convergence, is competitive with the other methods, both for natural color and graphic images. Additionally, the resulting palettes show interesting topological relationships among colors
This paper presents a new in-vehicle real-time vehicle detection strategy which hypothesizes the ... more This paper presents a new in-vehicle real-time vehicle detection strategy which hypothesizes the presence of vehicles in rectangular sub-regions based on the robust classification of features vectors result of a combination of multiple morphological vehicle features. One vector is extracted for each region of the image likely containing vehicles as a multidimensional likelihood measure with respect to a simplified vehicle model. A supervised training phase set the representative vectors of the classes vehicle and non-vehicle, so that the hypothesis is verified or not according to the Mahalanobis distance between the feature vector and the representative vectors. Excellent results have been obtained in several video sequences accurately detecting vehicles with very different aspect-ratio, color, size, etc, while minimizing the number of missing detections and false alarms.
Fatalities and injuries connected with road accidents and its social and economic implications ar... more 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 monitor and recognize the road environment and the driver's state in real time using data obtained from three types of sources: the in-vehicle sensing system, the road infrastructure and neighbouring cars. It supports both, road-to-vehicle and vehicle-to-vehicle communication in order to enhance drivers' perception on road environment and improve responses in critical scenarios. This work addresses the I-WAY technical solution and its overall architecture.
This paper presents a system which automatically detects moving targets contained in aerial seque... more This paper presents a system which automatically detects moving targets contained in aerial sequences of FLIR images under heavy cluttered conditions. In these situations, the detection of moving targets is generally carried out through the implementation of segmentation ...
An efficient automatic moving target detection and tracking system in airborne forward looking in... more An efficient automatic moving target detection and tracking system in airborne forward looking infrared (FLIR) imagery is presented in this paper. Due to camera ego-motion, these detection and tracking tasks are challenging problems. Besides, previously proposed techniques are not suitable for aerial images, as the predominant regions are non-textured. The proposed system efficiently estimates not only the camera motion but also the target motion, by means of an accurate motion vector field computation and robust motion parameters estimation technique. This information allows accurately to segment each target, and tracking them with ego-motion compensation. Verification of tracking restrictions helps detecting true targets while reducing very significantly the false alarm rate. Excellent results have been obtained over real FLIR sequences.
In this paper we propose a new fast mode decision (FMD) algorithm to reduce the computational loa... more In this paper we propose a new fast mode decision (FMD) algorithm to reduce the computational load of the motion estimation (ME) process of the new video coding standard H.264/AVC Main Profile. The algorithm firstly computes the Skip/Direct Mode (respectively for P and B-frames), for all macroblocks (MBs), and then decides, for each MB if no mores modes are needed. This decision is based on the generation of predictions of the expected PSNR of the frame to be encoded. These predictions are performed with the distortion cost obtained for Skip/Direct Mode jointly with the average distortion cost obtained for the previous encoded frames. Results show that the computational load have been dramatically reduced, with average encoding time saving of -36.38%, while nearly negligible loss of coding efficiency.
This paper presents an innovative road modeling strategy for video-based driver assistance system... more 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, such as computing linear models of the road, extraction of calibration parameters of the camera, stabilization of sequences, etc. In this work, a novel strategy for vanishing point estimation is presented. It is based on the use of an adaptive steerable filter bank which enhances lane markings according to their expected orientations. Very accurate results are obtained in the computation of the vanishing point for several type of sequences, including overtaking traffic, changing illumination conditions, paintings in the road, etc.
In this paper we propose a new fast mode decision (FMD) algorithm for H.264/AVC to reduce the com... more In this paper we propose a new fast mode decision (FMD) algorithm for H.264/AVC to reduce the computational load of the motion estimation (ME) process. It is oriented to dramatically reduce the encoding time regardless of the level of motion present at the sequences (high or lowmotion). The algorithm decides as the best mode the SKIP Mode or Mode 1 without need to compute the rest of coding alternatives if some conditions are satisfied. These conditions ensure these modes to be used appropriately for low motion and high motion sequences respectively to achieve an appropriate rate distortion (RD) cost based on the results of the previous encoded frames. Tests have shown reductions of the encoding time around -81% for all kinds of sequences, while moderate loss of coding efficiency.
This paper presents a robust method for real-time vehicle detection and tracking in dynamic traff... more This paper presents a robust method for real-time vehicle detection and tracking in dynamic trafflc environments. The proposed strategy aims to find a trade-off between the robustness shown by timeuncorrelated detection techniques and the speed-up obtained with tracking algorithms. It combines both advantages by continuously evaluating the quality of the tracking results along time and triggering new detections to restart the tracking process when quality falls behind a certain quality requirement. Robustness is also ensured within the tracking algorithm with an outlier rejection stage and the use of stochastic flltering. Several sequences from real trafflc situations have been tested, obtaining highly accurate múltiple vehicle detections.
People positioning and tracking in 3D indoor environments are challenging tasks due to background... more 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 tracking system is presented, which shows itself robust to both possible occlusion sources: static scene objects and other people. The system holds on a set of multiple cameras with partially overlapped fields of view. Moving regions are segmented independently in each camera stream by means of a new background modeling strategy based on Gabor filters. People detection is carried out on these segmentations through a template-based correlation strategy. Detected people are tracked independently in each camera view by means of a graph-based matching strategy, which estimates the best correspondences between consecutive people segmentations. Finally, 3D tracking and positioning of people is achieved by geometrical consistency analysis over the tracked 2D candidates, using head position (instead of object centroids) to increase robustness to foreground occlusions.
In this work, a new inverse perspective mapping (IPM) technique is proposed based on a robust est... more 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 moving vehicle suffer. The estimation of the vanishing point relies on a novel and efficient feature extraction strategy, which segmentates the lane markings of the images by combining a histogram-based segmentation with temporal and frequency filtering. Then, the vanishing point of each image is stabilized by means of a temporal filtering along the estimates of previous images. In a last step, the IPM image is computed based on the stabilized vanishing point. Tests have been carried out on several long video sequences captured from cameras inside a vehicle being driven along highways and local roads, with different illumination and weather conditions, presence of shadows, occluding vehicles, and slope changes. Results have shown a significant improvement in terms of lane width constancy and parallelism between lane markings over non-stabilized IPM algorithms.
Road modeling is the first step towards environment perception within driver assistance video-bas... more Road modeling is the first step towards environment perception within driver assistance video-based systems. Typically, lañe modeling allows applications such as lañe departure warning or lañe invasión by other vehicles. In this paper, a new monocular image processing strategy that achieves a robust múltiple lañe model is proposed. The identification of múltiple lañes is done by firstly detecting the own lañe and estimating its geometry under perspective distortion. The perspective analysis and curve fitting allows to hypothesize adjacent lañes assuming some a priori knowledge about the road. The verification of these hypotheses is carried out by a confidence level analysis. Several types of sequences have been tested, with different illumination conditions, presence of shadows and significant curvature, all performing in realtime. Results show the robustness of the system, delivering accurate múltiple lañe road models in most situations.
ABSTRACT This paper presents the architecture of a system to provide user orientation with the ca... more ABSTRACT This paper presents the architecture of a system to provide user orientation with the capability to automatically show multimedia information (audio, static images, panoramic images, VRML models, HTML pages) according to the user real or virtual location within a ...
In spite of their advantages, region-based approaches present a heavy burden in the required amou... more In spite of their advantages, region-based approaches present a heavy burden in the required amount of information to describe region contours. To avoid these limitations, a new region-based motion estimation and compensation strategy is proposed, which allows the operation on arbitrary shaped regions and the ability to reconstruct them without any contour information. The strategy is enhanced by the use of multivector motion estimation and compensation. Results showing the quality and advantages of the strategy are provided
A new method for the determination of adaptive palettes of color images with a variation of Kohon... more A new method for the determination of adaptive palettes of color images with a variation of Kohonen (1984) networks, for the purposes of image storage and display, is presented. New neighborhood relationships in one and three dimensions are defined among neurons and the scope of these binds is also extended. The presented method is compared with popular palette selection algorithms, the resulting quality, provided network convergence, is competitive with the other methods, both for natural color and graphic images. Additionally, the resulting palettes show interesting topological relationships among colors
This paper presents a new in-vehicle real-time vehicle detection strategy which hypothesizes the ... more This paper presents a new in-vehicle real-time vehicle detection strategy which hypothesizes the presence of vehicles in rectangular sub-regions based on the robust classification of features vectors result of a combination of multiple morphological vehicle features. One vector is extracted for each region of the image likely containing vehicles as a multidimensional likelihood measure with respect to a simplified vehicle model. A supervised training phase set the representative vectors of the classes vehicle and non-vehicle, so that the hypothesis is verified or not according to the Mahalanobis distance between the feature vector and the representative vectors. Excellent results have been obtained in several video sequences accurately detecting vehicles with very different aspect-ratio, color, size, etc, while minimizing the number of missing detections and false alarms.
Fatalities and injuries connected with road accidents and its social and economic implications ar... more 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 monitor and recognize the road environment and the driver's state in real time using data obtained from three types of sources: the in-vehicle sensing system, the road infrastructure and neighbouring cars. It supports both, road-to-vehicle and vehicle-to-vehicle communication in order to enhance drivers' perception on road environment and improve responses in critical scenarios. This work addresses the I-WAY technical solution and its overall architecture.
This paper presents a system which automatically detects moving targets contained in aerial seque... more This paper presents a system which automatically detects moving targets contained in aerial sequences of FLIR images under heavy cluttered conditions. In these situations, the detection of moving targets is generally carried out through the implementation of segmentation ...
An efficient automatic moving target detection and tracking system in airborne forward looking in... more An efficient automatic moving target detection and tracking system in airborne forward looking infrared (FLIR) imagery is presented in this paper. Due to camera ego-motion, these detection and tracking tasks are challenging problems. Besides, previously proposed techniques are not suitable for aerial images, as the predominant regions are non-textured. The proposed system efficiently estimates not only the camera motion but also the target motion, by means of an accurate motion vector field computation and robust motion parameters estimation technique. This information allows accurately to segment each target, and tracking them with ego-motion compensation. Verification of tracking restrictions helps detecting true targets while reducing very significantly the false alarm rate. Excellent results have been obtained over real FLIR sequences.
In this paper we propose a new fast mode decision (FMD) algorithm to reduce the computational loa... more In this paper we propose a new fast mode decision (FMD) algorithm to reduce the computational load of the motion estimation (ME) process of the new video coding standard H.264/AVC Main Profile. The algorithm firstly computes the Skip/Direct Mode (respectively for P and B-frames), for all macroblocks (MBs), and then decides, for each MB if no mores modes are needed. This decision is based on the generation of predictions of the expected PSNR of the frame to be encoded. These predictions are performed with the distortion cost obtained for Skip/Direct Mode jointly with the average distortion cost obtained for the previous encoded frames. Results show that the computational load have been dramatically reduced, with average encoding time saving of -36.38%, while nearly negligible loss of coding efficiency.
This paper presents an innovative road modeling strategy for video-based driver assistance system... more 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, such as computing linear models of the road, extraction of calibration parameters of the camera, stabilization of sequences, etc. In this work, a novel strategy for vanishing point estimation is presented. It is based on the use of an adaptive steerable filter bank which enhances lane markings according to their expected orientations. Very accurate results are obtained in the computation of the vanishing point for several type of sequences, including overtaking traffic, changing illumination conditions, paintings in the road, etc.
In this paper we propose a new fast mode decision (FMD) algorithm for H.264/AVC to reduce the com... more In this paper we propose a new fast mode decision (FMD) algorithm for H.264/AVC to reduce the computational load of the motion estimation (ME) process. It is oriented to dramatically reduce the encoding time regardless of the level of motion present at the sequences (high or lowmotion). The algorithm decides as the best mode the SKIP Mode or Mode 1 without need to compute the rest of coding alternatives if some conditions are satisfied. These conditions ensure these modes to be used appropriately for low motion and high motion sequences respectively to achieve an appropriate rate distortion (RD) cost based on the results of the previous encoded frames. Tests have shown reductions of the encoding time around -81% for all kinds of sequences, while moderate loss of coding efficiency.
This paper presents a robust method for real-time vehicle detection and tracking in dynamic traff... more This paper presents a robust method for real-time vehicle detection and tracking in dynamic trafflc environments. The proposed strategy aims to find a trade-off between the robustness shown by timeuncorrelated detection techniques and the speed-up obtained with tracking algorithms. It combines both advantages by continuously evaluating the quality of the tracking results along time and triggering new detections to restart the tracking process when quality falls behind a certain quality requirement. Robustness is also ensured within the tracking algorithm with an outlier rejection stage and the use of stochastic flltering. Several sequences from real trafflc situations have been tested, obtaining highly accurate múltiple vehicle detections.
People positioning and tracking in 3D indoor environments are challenging tasks due to background... more 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 tracking system is presented, which shows itself robust to both possible occlusion sources: static scene objects and other people. The system holds on a set of multiple cameras with partially overlapped fields of view. Moving regions are segmented independently in each camera stream by means of a new background modeling strategy based on Gabor filters. People detection is carried out on these segmentations through a template-based correlation strategy. Detected people are tracked independently in each camera view by means of a graph-based matching strategy, which estimates the best correspondences between consecutive people segmentations. Finally, 3D tracking and positioning of people is achieved by geometrical consistency analysis over the tracked 2D candidates, using head position (instead of object centroids) to increase robustness to foreground occlusions.
In this work, a new inverse perspective mapping (IPM) technique is proposed based on a robust est... more 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 moving vehicle suffer. The estimation of the vanishing point relies on a novel and efficient feature extraction strategy, which segmentates the lane markings of the images by combining a histogram-based segmentation with temporal and frequency filtering. Then, the vanishing point of each image is stabilized by means of a temporal filtering along the estimates of previous images. In a last step, the IPM image is computed based on the stabilized vanishing point. Tests have been carried out on several long video sequences captured from cameras inside a vehicle being driven along highways and local roads, with different illumination and weather conditions, presence of shadows, occluding vehicles, and slope changes. Results have shown a significant improvement in terms of lane width constancy and parallelism between lane markings over non-stabilized IPM algorithms.
Road modeling is the first step towards environment perception within driver assistance video-bas... more Road modeling is the first step towards environment perception within driver assistance video-based systems. Typically, lañe modeling allows applications such as lañe departure warning or lañe invasión by other vehicles. In this paper, a new monocular image processing strategy that achieves a robust múltiple lañe model is proposed. The identification of múltiple lañes is done by firstly detecting the own lañe and estimating its geometry under perspective distortion. The perspective analysis and curve fitting allows to hypothesize adjacent lañes assuming some a priori knowledge about the road. The verification of these hypotheses is carried out by a confidence level analysis. Several types of sequences have been tested, with different illumination conditions, presence of shadows and significant curvature, all performing in realtime. Results show the robustness of the system, delivering accurate múltiple lañe road models in most situations.
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