S. Bronte - Academia.edu (original) (raw)

Papers by S. Bronte

ABSTRACT Reading text from scene images is a challenging problem that is receiving much attention... more ABSTRACT Reading text from scene images is a challenging problem that is receiving much attention, especially since the appearance of imaging devices in low-cost consumer products like mobile phones. This paper presents an easy and fast method to recognize individual characters in images of natural scenes that is applied after an algorithm that robustly locates text on such images. The recognition is based on a gradient direction feature. Our approach also computes the output probability for each class of the character to be recognized. The proposed feature is compared to other features typically used in character recognition. Experimental results with a challenging dataset show the good performance of the proposed method.

ABSTRACT An automatic text recognizer needs, in first place, to localize the text in the image th... more ABSTRACT An automatic text recognizer needs, in first place, to localize the text in the image the more accurately possible. For this purpose, we present in this paper a robust method for text detection. It is composed of three main stages: a segmentation stage to find character candidates, a connected component analysis based on fast-to-compute but robust features to accept characters and discard non-text objects, and finally a text line classifier based on gradient features and support vector machines. Experimental results obtained with several challenging datasets show the good performance of the proposed method, which has been demonstrated to be more robust than using multi-scale computation or sliding windows.

Tracking non-rigid objects from video is useful in robotic systems such as HMIs or robotic manipu... more Tracking non-rigid objects from video is useful in robotic systems such as HMIs or robotic manipulator arms which interact with deformable objects. This paper proposes a method for sequential model-based 3D reconstruction of deformable objects and camera localization in real time. Nonrigid SFM methods commonly process a video sequence offline in a batch way. While there are real-time methods for rigid models, reconstruction of deformable 3D shapes for real-time applications is still unsolved. Dense approaches offer promising results, but processing all frames in batch, offline. We propose a real-time non-rigid reconstruction method based on a known deformable model. Object shape and pose is tracked by realtime estimation of camera pose and deformation coefficients. An extensive evaluation of the algorithm on several data sets, and comparison with state-of-the-art techniques is performed. The tests include different outlier rates, noise levels and occlusions handling.

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2009

In this document, a real-time fog detection system using an on-board low cost b&w camera, for a d... more In this document, a real-time fog detection system using an on-board low cost b&w camera, for a driving application, is presented. This system is based on two clues: estimation of the visibility distance, which is calculated from the camera projection equations and the blurring due to the fog. Because of the water particles floating in the air, sky light gets diffuse and, focus on the road zone, which is one of the darkest zones on the image. The apparent effect is that some part of the sky introduces in the road. Also in foggy scenes, the border strength is reduced in the upper part of the image. These two sources of information are used to make this system more robust. The final purpose of this system is to develop an automatic vision-based diagnostic system for warning ADAS of possible wrong working conditions. Some experimental results and the conclusions about this work are presented.

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014

We present a novel approach for place recognition and loop closure detection based on binary code... more We present a novel approach for place recognition and loop closure detection based on binary codes and disparity information using stereo images. Our method (ABLE-S) applies the Local Difference Binary (LDB) descriptor in a global framework to obtain a robust global image description, which is initially based on intensity and gradient pairwise comparisons. LDB has a higher descriptiveness power than other popular alternatives such as BRIEF, which only relies on intensity. In addition, we integrate disparity information into the binary descriptor (D-LDB). Disparity provides valuable information which decreases the effect of some typical problems in place recognition such as perceptual aliasing.

Sensors, 2014

This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of... more This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS). An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study.

Resumen—En este documento se presenta un sistema para el reconocimiento facial de conductores a b... more Resumen—En este documento se presenta un sistema para el reconocimiento facial de conductores a bordo de vehículos, con objeto final de diseñar un control del encendido en función de la identidad del conductor, que ha de estar dentro de un conjunto de usuarios ...

13th International IEEE Conference on Intelligent Transportation Systems, 2010

This paper presents a nonintrusive approach for monitoring driver drowsiness, based on computer v... more This paper presents a nonintrusive approach for monitoring driver drowsiness, based on computer vision techniques, installed in a realistic driving simulator. An IR stereo camera is placed in from of the driver in order to obtain PERCLOS, the most confident drowsiness parameter [1], in real-time and in a robust and automatic way. Our proposal doesn't need a calibration process and includes three main stages. The first is the pre-processing stage, which includes face and eye detection based on appearance strategy using the Viola and Jones algorithm, and the equalization of the eyes using a Hat transformation. An eye tracking strategy in a sequence of image frames is then carried out. The second stage executes the pupil position extraction and its characterization using integral projection techniques and a Gaussian model. The final stage executes the PERCLOS estimation, depending on the eyes closed rate on duration of time interval and fusing information obtained for each eye in the two images of the stereo camera. For evaluation of the proposed system several experiments have been designed by psychologists and carried out. A preliminary study about the performance of the proposal, based on confusion matrixes, is presented.

ABSTRACT Reading text from scene images is a challenging problem that is receiving much attention... more ABSTRACT Reading text from scene images is a challenging problem that is receiving much attention, especially since the appearance of imaging devices in low-cost consumer products like mobile phones. This paper presents an easy and fast method to recognize individual characters in images of natural scenes that is applied after an algorithm that robustly locates text on such images. The recognition is based on a gradient direction feature. Our approach also computes the output probability for each class of the character to be recognized. The proposed feature is compared to other features typically used in character recognition. Experimental results with a challenging dataset show the good performance of the proposed method.

ABSTRACT An automatic text recognizer needs, in first place, to localize the text in the image th... more ABSTRACT An automatic text recognizer needs, in first place, to localize the text in the image the more accurately possible. For this purpose, we present in this paper a robust method for text detection. It is composed of three main stages: a segmentation stage to find character candidates, a connected component analysis based on fast-to-compute but robust features to accept characters and discard non-text objects, and finally a text line classifier based on gradient features and support vector machines. Experimental results obtained with several challenging datasets show the good performance of the proposed method, which has been demonstrated to be more robust than using multi-scale computation or sliding windows.

Tracking non-rigid objects from video is useful in robotic systems such as HMIs or robotic manipu... more Tracking non-rigid objects from video is useful in robotic systems such as HMIs or robotic manipulator arms which interact with deformable objects. This paper proposes a method for sequential model-based 3D reconstruction of deformable objects and camera localization in real time. Nonrigid SFM methods commonly process a video sequence offline in a batch way. While there are real-time methods for rigid models, reconstruction of deformable 3D shapes for real-time applications is still unsolved. Dense approaches offer promising results, but processing all frames in batch, offline. We propose a real-time non-rigid reconstruction method based on a known deformable model. Object shape and pose is tracked by realtime estimation of camera pose and deformation coefficients. An extensive evaluation of the algorithm on several data sets, and comparison with state-of-the-art techniques is performed. The tests include different outlier rates, noise levels and occlusions handling.

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2009

In this document, a real-time fog detection system using an on-board low cost b&w camera, for a d... more In this document, a real-time fog detection system using an on-board low cost b&w camera, for a driving application, is presented. This system is based on two clues: estimation of the visibility distance, which is calculated from the camera projection equations and the blurring due to the fog. Because of the water particles floating in the air, sky light gets diffuse and, focus on the road zone, which is one of the darkest zones on the image. The apparent effect is that some part of the sky introduces in the road. Also in foggy scenes, the border strength is reduced in the upper part of the image. These two sources of information are used to make this system more robust. The final purpose of this system is to develop an automatic vision-based diagnostic system for warning ADAS of possible wrong working conditions. Some experimental results and the conclusions about this work are presented.

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014

We present a novel approach for place recognition and loop closure detection based on binary code... more We present a novel approach for place recognition and loop closure detection based on binary codes and disparity information using stereo images. Our method (ABLE-S) applies the Local Difference Binary (LDB) descriptor in a global framework to obtain a robust global image description, which is initially based on intensity and gradient pairwise comparisons. LDB has a higher descriptiveness power than other popular alternatives such as BRIEF, which only relies on intensity. In addition, we integrate disparity information into the binary descriptor (D-LDB). Disparity provides valuable information which decreases the effect of some typical problems in place recognition such as perceptual aliasing.

Sensors, 2014

This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of... more This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS). An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study.

Resumen—En este documento se presenta un sistema para el reconocimiento facial de conductores a b... more Resumen—En este documento se presenta un sistema para el reconocimiento facial de conductores a bordo de vehículos, con objeto final de diseñar un control del encendido en función de la identidad del conductor, que ha de estar dentro de un conjunto de usuarios ...

13th International IEEE Conference on Intelligent Transportation Systems, 2010

This paper presents a nonintrusive approach for monitoring driver drowsiness, based on computer v... more This paper presents a nonintrusive approach for monitoring driver drowsiness, based on computer vision techniques, installed in a realistic driving simulator. An IR stereo camera is placed in from of the driver in order to obtain PERCLOS, the most confident drowsiness parameter [1], in real-time and in a robust and automatic way. Our proposal doesn't need a calibration process and includes three main stages. The first is the pre-processing stage, which includes face and eye detection based on appearance strategy using the Viola and Jones algorithm, and the equalization of the eyes using a Hat transformation. An eye tracking strategy in a sequence of image frames is then carried out. The second stage executes the pupil position extraction and its characterization using integral projection techniques and a Gaussian model. The final stage executes the PERCLOS estimation, depending on the eyes closed rate on duration of time interval and fusing information obtained for each eye in the two images of the stereo camera. For evaluation of the proposed system several experiments have been designed by psychologists and carried out. A preliminary study about the performance of the proposal, based on confusion matrixes, is presented.