Real-time architecture for robust motion estimation under varying illumination conditions

Motion estimation from image sequences is a complex problem which requires high computing resources and is highly affected by changes in the illumination conditions in most of the existing approaches. In this contribution we present a high performance system that deals with this limitation. Robustness to varying illumination conditions is achieved by a novel technique that combines a gradient-based optical flow method with a non-parametric image transformation based on the Rank transform. The paper describes this method and quantitatively evaluates its robustness to different illumination changing patterns. This technique has been successfully implemented in a real-time system using reconfigurable hardware. Our contribution presents the computing architecture, including the resources consumption and the obtained performance. The final system is a real-time device capable to computing motion sequences in real-time even in conditions with significant illumination changes. The robustness of the proposed system facilitates its use in multiple potential application fields.This work has been supported by the grants DEPROVI (DPI2004-07032), DRIVSCO (IST-016276-2) and TIC2007:”Plataforma Sw-Hw para sistemas de visión 3D en tiempo real”

Performance evaluation and limitations of a vision system on a reconfigurable/programmable chip

This paper presents a survey of the characteristics of a vision system implemented in a reconfigurable/programmable chip (FPGA). System limitations and performance have been evaluated in order to derive specifications and constraints for further vision system synthesis. The system hereby reported has a conventional architecture. It consists in a central microprocessor (CPU) and the necessary peripheral elements for data acquisition, data storage and communications. It has been designed to stand alone, but a link to the programming and debugging tools running in a digital host (PC) is provided. In order to alleviate the computational load of the central microprocessor, we have designed a visual co-processor in charge of the low-level image processing tasks. It operates autonomously, commanded by the CPU, as another system peripheral. The complete system, without the sensor, has been implemented in a single reconfigurable chip as a SOPC. The incorporation of a dedicated visual co-processor, with specific circuitry for low-level image processing acceleration, enhances the system throughput outperforming conventional processing schemes. However, timemultiplexing of the dedicated hardware remains a limiting factor for the achievable peak computing power. We have quantified this effect and sketched possible solutions, like replication of the specific image processing hardware

Performance evaluation and limitations of a vision system on a reconfigurable/programmable chip

This paper presents a survey of the characteristics of a vision system implemented in a reconfigurable/programmable chip (FPGA). System limitations and performance have been evaluated in order to derive specifications and constraints for further vision system synthesis. The system hereby reported has a conventional architecture. It consists in a central microprocessor (CPU) and the necessary peripheral elements for data acquisition, data storage and communications. It has been designed to stand alone, but a link to the programming and debugging tools running in a digital host (PC) is provided. In order to alleviate the computational load of the central microprocessor, we have designed a visual co-processor in charge of the low-level image processing tasks. It operates autonomously, commanded by the CPU, as another system peripheral. The complete system, without the sensor, has been implemented in a single reconfigurable chip as a SOPC. The incorporation of a dedicated visual co-processor, with specific circuitry for low-level image processing acceleration, enhances the system throughput outperforming conventional processing schemes. However, time-multiplexing of the dedicated hardware remains a limiting factor for the achievable peak computing power. We have quantified this effect and sketched possible solutions, like replication of the specific image processing hardware. © J.UCS.This work has been partially funded by project FIT-330100-2005-162 of the Spanish Ministry of Industry, Tourism and Commerce. The work of F. J. Sánchez-Fernández is supported by a grant of the Spanish Ministry of Education and Science.Peer Reviewe

Development of a text reading system on video images

Since the early days of computer science researchers sought to devise a machine which could automatically read text to help people with visual impairments. The problem of extracting and recognising text on document images has been largely resolved, but reading text from images of natural scenes remains a challenge. Scene text can present uneven lighting, complex backgrounds or perspective and lens distortion; it usually appears as short sentences or isolated words and shows a very diverse set of typefaces. However, video sequences of natural scenes provide a temporal redundancy that can be exploited to compensate for some of these deficiencies. Here we present a complete end-to-end, real-time scene text reading system on video images based on perspective aware text tracking. The main contribution of this work is a system that automatically detects, recognises and tracks text in videos of natural scenes in real-time. The focus of our method is on large text found in outdoor environments, such as shop signs, street names and billboards. We introduce novel efficient techniques for text detection, text aggregation and text perspective estimation. Furthermore, we propose using a set of Unscented Kalman Filters (UKF) to maintain each text region¿s identity and to continuously track the homography transformation of the text into a fronto-parallel view, thereby being resilient to erratic camera motion and wide baseline changes in orientation. The orientation of each text line is estimated using a method that relies on the geometry of the characters themselves to estimate a rectifying homography. This is done irrespective of the view of the text over a large range of orientations. We also demonstrate a wearable head-mounted device for text reading that encases a camera for image acquisition and a pair of headphones for synthesized speech output. Our system is designed for continuous and unsupervised operation over long periods of time. It is completely automatic and features quick failure recovery and interactive text reading. It is also highly parallelised in order to maximize the usage of available processing power and to achieve real-time operation. We show comparative results that improve the current state-of-the-art when correcting perspective deformation of scene text. The end-to-end system performance is demonstrated on sequences recorded in outdoor scenarios. Finally, we also release a dataset of text tracking videos along with the annotated ground-truth of text regions

Driver Behaviour and Road Safety Analysis Using Computer Vision and Applications in Roundabout Safety

RÉSUMÉ L’un des principaux défis provenant de l’analyse traditionnelle de la sécurité routière basée sur les données historiques d’accidents est le besoin d’observer de véritables collisions entre les usagers de la route. Non seulement indésirables, ces collisions sont difficiles à observer. À cet effet, les méthodes d’analyse substitutive de la sécurité routière gagnent du terrain dans le milieu de la recherche en tant qu’alternative proactive à l’observation de ces accidents de la route : cette approche promet de modéliser indirectement les collisions par l’intermédiaire de précurseurs de collisions pouvant être retrouvés dans des données de circulation ordinaire : situations de trajectoire de collision, quasi-accidents, conflits de circulation, etc. En sus, l’analyse substitutive de la sécurité donne également les chercheurs un aperçu des mécanismes de collision, ce qui permettrait de mieux comprendre les facteurs favorisant les accidents. Cependant, un grand nombre de définition de ces situations précurseures de collision, ainsi que des problèmes de cohérence et de subjectivité des méthodes de collecte de données ont entravé l’adoption des méthodes d’analyse substitutive de la sécurité routière.----------ABSTRACT One of the main challenges of traditional road safety analysis based on historical accident records is its dependence on the occurrence and subsequent observation of real traffic collisions. Traffic collisions are not only undesirable, they are difficult to observe. Surrogate safety analysis is gaining traction in the research community as a proactive alternative to observing historical accident records. With this approach, collisions are instead predicted indirectly via precursors to collisions found in everyday traffic scenarios: collision-courses, near-misses, traffic conflicts, etc. Furthermore, the scope of surrogate safety analysis provides insight into collision mechanisms, allowing for better investigative procedures. However, the wide range of collision precursor definitions, and issues with inconsistent or sometimes subjective data collection methods have hampered surrogate safety analysis adoption

Fast Adaptive Augmented Lagrangian Digital Image Correlation

Digital image correlation (DIC) is a powerful experimental technique for measuring full-field displacement and strain. The basic idea of the method is to compare images of an object decorated with a speckle pattern before and after deformation in order to compute the displacement and strain fields. Local Subset DIC and finite element-based Global DIC are two widely used image matching methods; however there are some drawbacks to these methods. In Local Subset DIC, the computed displacement field may not satisfy compatibility, and the deformation gradient may be noisy, especially when the subset size is small. Global DIC incorporates displacement compatibility, but can be computationally expensive. In this thesis, we propose a new method, the augmented-Lagrangian digital image correlation (ALDIC), that combines the advantages of both the local (fast and in parallel) and global (compatible) methods. We demonstrate that ALDIC has higher accuracy and behaves more robustly compared to both Local Subset DIC and Global DIC. DIC requires a large number of high resolution images, which imposes significant needs on data storage and transmission. We combined DIC algorithms with image compression techniques and show that it is possible to obtain accurate displace- ment and strain fields with only 5 % of the original image size. We studied two compression techniques – discrete cosine transform (DCT) and wavelet transform, and three DIC algorithms – Local Subset DIC, Global DIC and our newly proposed augmented Lagrangian DIC (ALDIC). We found the Local Subset DIC leads to the largest errors and ALDIC to the smallest when compressed images are used. We also found wavelet-based image compression introduces less error compared to DCT image compression. To further speed up and improve the accuracy of DIC algorithms, especially in the study of complex heterogeneous strain fields at various length scales, we apply an adaptive finite element mesh to DIC methods. We develop a new h-adaptive technique and apply it to ALDIC. We show that this adaptive mesh ALDIC algorithm significantly decreases computation time with no loss (and some gain) in accuracy.</p

Problèmes inverses d'hémodynamique. Estimation rapide des flux sanguins à partir de données médicales

This thesis presents a work at the interface between applied mathematics and biomedical engineering. The work’s main subject is the estimation of blood flows and quantities of medical interest in diagnosing certain diseases concerning the cardiovascular system. We propose a complete pipeline, providing the theoretical foundations for state estimation from medical data using reduced-order models, and addressing inter-patient variability. Extensive numerical tests are shown in realistic 3D scenarios that verify the potential impact of the work in the medical comunnity.Cette thèse présente un travail à l’interface entre les mathématiques appliquées et l’ingénierie biomedicale. Le sujet principal en est l’estimation des écoulements sanguins et de quantités d’intérêt pour le diagnostic de certaines maladies cardiovasculaires. Nous proposons une procédure complète, dont nous détaillons les fondements théoriques, permettant l’estimation d’état à partir de données médicales en utilisant des techniques de réduction de modèle, et en prenant en compte la problématique de la variabilité inter-patients. De nombreux test numériques en 3D sont exposés afin de vérifier le potentiel de cette étude dans le domaine médical