Vision systems have become ubiquitous. They are used for traffic monitoring, elderly care, video conferencing, virtual reality, surveillance, smart rooms, home automation, sport games analysis, industrial safety, medical care etc. In most vision systems, the data coming from the visual sensor(s) is processed before transmission in order to save communication bandwidth or achieve higher frame rates. The type of data processing needs to be chosen carefully depending on the targeted application, and taking into account the available memory, computational power, energy resources and bandwidth constraints. In this dissertation, we investigate how a vision system should be built under practical constraints. First, this system should be intelligent, such that the right data is extracted from the video source. Second, when processing video data this intelligent vision system should know its own practical limitations, and should try to achieve the best possible output result that lies within its capabilities. We study and improve a wide range of vision systems for a variety of applications, which go together with different types of constraints. First, we present a modulo-PCM-based coding algorithm for applications that demand very low complexity coding and need to preserve some of the advantageous properties of PCM coding (direct processing, random access, rate scalability). Our modulo-PCM coding scheme combines three well-known, simple, source coding strategies: PCM, binning, and interpolative coding. The encoder first analyzes the signal statistics in a very simple way. Then, based on these signal statistics, the encoder simply discards a number of bits of each image sample. The modulo-PCM decoder recovers the removed bits of each sample by using its received bits and side information which is generated by interpolating previous decoded signals. Our algorithm is especially appropriate for image coding. / Morbee, M. (2011). Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/12126 / Palancia

L’intralogistique (ou logistique interne) s’intéresse au traitement et à l’optimisation des flux physiques au sein des entrepôts, centres de distribution et usines. Les systèmes de manutention automatisés sont au cœur de la logistique interne de plusieurs industries comme le commerce en ligne, la messagerie postale, la grande distribution, l’industrie manufacturière, le transport aéroportuaire, etc. Ces équipements composés de lignes de convoyage haute cadence permettent un transport sûr et fiable d’un volume considérable de biens et de marchandises tout en réduisant les coûts.L’automatisation de l’acheminement des flux physiques par les systèmes de manutention repose sur l’identification et le suivi en temps réel des charges transportées. Dans cette thèse, nous explorons une solution de suivi qui emploie un réseau de caméras intelligentes à champs recouvrants. L’objectif final étant de fournir l’information de suivi sur les charges transportées pour le pilotage d’un système de manutention.Le suivi d’objets est un problème fondamental de la vision par ordinateur qui a de nombreuses applications comme la vidéosurveillance, la robotique, les voitures autonomes, etc. Nous avons intégré plusieurs briques de base issues de la vidéosurveillance et traditionnellement appliquées aux scènes de surveillance automobile ou de surveillance des activités humaines pour constituer une chaine de suivi de référence. Cette chaine d’analyse vidéo étalon nous a permis de caractériser des hypothèses propres au convoyage d’objet. Nous proposons dans cette thèse d’incorporer cette connaissance métier dans la chaine de suivi pour en améliorer les performances. Nous avons, notamment pris en compte, dans l’étape de segmentation des images, le fait que les objets doivent pouvoir s’arrêter sans pour autant être intégrés aux modèles d’arrière-plan. Nous avons également exploité la régularité des trajectoires des objets convoyés dans les installations, permettant d’améliorer les modèles prédictifs de la position et de la vitesse des objets, dans les étapes de suivi. Enfin, nous avons intégré des contraintes de stricte monotonie dans l’ordre des colis sur le convoyeur, contraintes qui n’existent pas dans les scènes généralistes, pour ré-identifier les objets dans les situations où ils sont proches des eux les autres.Nous nous sommes par ailleurs attelés à un problème pratique d’optimisation des performances sur l’architecture multi-cœurs couplée aux caméras intelligentes. Dans ce cadre, nous avons a mis en place un apprentissage dynamique de la zone de l’image contenant le convoyeur. Cette zone d’intérêt nous a permis de limiter la mise à jour du modèle de fond à cette seule zone. Nous avons, par la suite, proposé une stratégie de parallélisation qui partitionne de manière adaptative cette région d’intérêt de l’image, afin d’équilibrer au mieux la charge de travail entre les différents cœurs de l’architecture des caméras intelligentes.Nous avons également traité la problématique du suivi sur plusieurs caméras. Nous avons proposé une approche basée sur un système de composition d’évènements. Cette approche nous a permis de fusionner les données de suivi local pour former les trajectoires globales des colis, tout en intégrant des informations issues du processus métier, par exemple la saisie de l’information de destination par des opérateurs sur un terminal avant la dépose des colis. Nous avons validé cette approche sur un système de manutention mis en place dans un centre de tri postal de grande envergure. Le réseau de caméras déployé est composé de 32 caméras qui assurent le suivi de plus de 400.000 colis/jour sur des lignes de dépose. Le taux d’erreur du suivi obtenu est inférieur à 1 colis sur 1000 (0,1%). / Intralogistics (or internal logistics) focuses on the management and optimization of internal production and distribution processes within warehouses, distribution centers, and factories. Automated handling systems play a crucial role in the internal logistics of several industries such as e-commerce, postal messaging, retail, manufacturing, airport transport, etc. These systems are composed by multiple high-speed conveyor lines that provide safe and reliable transportation of a large volume of goods and merchandise while reducing costs.The automation of the conveying process relies on the identification and the real-time tracking of the transported loads. In this thesis, we designed a tracking solution that employs a network of smart cameras with an overlapping field of view. The goal is to provide tracking information to control an automated handling system.Multiple object tracking is a fundamental problem of computer vision that has many applications such as video surveillance, robotics, autonomous cars, etc. We integrated several building blocks traditionally applied to traffic surveillance or human activities monitoring to constitute a tracking pipeline. We used this baseline tracking pipeline to characterize contextual scene information proper to the conveying scenario. We integrated this contextual information to the tracking pipeline to enhance the performance. In particular, we took into account the state of moving objects that become stationary in the background subtraction step to prevent their absorption to the background model. We have also exploited the regularity of objects trajectory to enhance the motion model associated with the tracked objects. Finally, we integrated the precedence ordering constraint among the conveyed object to reidentify them when they are close to each other.We have also tackled practical problems related to the optimization the execution of the proposed tracking problem in the multi-core architectures of smart cameras. In particular, we proposed a dynamic learning process that extracts the region of the image that corresponds to the conveyor lines. We reduced the number of the processed pixel by restricting the processing to this region of interest. We also proposed a parallelization strategy that adaptively partitions this region of interest of the image, in order to balance the workload between the different cores of the smart cameras.Finally, we proposed a multiple cameras tracking algorithms based on event composition. This approach fuses the local tracking generated by the smart cameras to form global object trajectories and information from third party systems such as the destination of the object entered by operators on a terminal. We validated the proposed approach for the control of a sorting system deployed in a postal distribution warehouse. A network of cameras composed of 32 cameras tracks more than 400.000 parcel/day in injections lines. The tracking error rate is less than 1 parcel in a 1000 (0.1%).

Les systèmes de vision artificielle sont aujourd'hui limités à l'extraction de données issues de ce que les caméras « voient ». Cependant, la compréhension de ce qu'elles voient peut être enrichie en associant la connaissance du contexte et la connaissance d'interprétation d'un humain.Dans ces travaux de thèse, nous proposons une approche associant des algorithmes de vision atificielle à une modélisation sémantique du contexte d'acquisition.Cette approche permet de réaliser un raisonnement sur la connaissance extraite des images par les caméras en temps réel. Ce raisonnement offre une réponse aux problèmes d'occlusion et d'erreurs de détections inhérents aux algorithmes de vision artificielle. Le système complet permet d'offrir un ensemble de services intelligents (guidage, comptage...) tout en respectant la vie privée des personnes observées. Ces travaux forment la première étape du développement d'un bâtiment intelligent qui peut automatiquement réagir et évoluer en observant l'activité de ces usagers, i.e., un bâtiment intelligent qui prend en compte les informations contextuelles.Le résultat, nommé WiseNET, est une intelligence artificielle en charge des décisions au niveau du bâtiment (qui pourrait être étendu à un groupe de bâtiments ou même a l'échelle d'un ville intelligente). Elle est aussi capable de dialoguer avec l'utilisateur ou l'administrateur humain de manière explicite. / To date, computer vision systems are limited to extract digital data of what the cameras "see". However, the meaning of what they observe could be greatly enhanced by environment and human-skills knowledge.In this work, we propose a new approach to cross-fertilize computer vision with contextual information, based on semantic modelization defined by an expert.This approach extracts the knowledge from images and uses it to perform real-time reasoning according to the contextual information, events of interest and logic rules. The reasoning with image knowledge allows to overcome some problems of computer vision such as occlusion and missed detections and to offer services such as people guidance and people counting. The proposed approach is the first step to develop an "all-seeing" smart building that can automatically react according to its evolving information, i.e., a context-aware smart building.The proposed framework, named WiseNET, is an artificial intelligence (AI) that is in charge of taking decisions in a smart building (which can be extended to a group of buildings or even a smart city). This AI enables the communication between the building itself and its users to be achieved by using a language understandable by humans.

Human-wildlife conflict continues to grow as a concern across the world. The conflict is experienced in many different forms and it has become persistent on the pastoral lands that are situated closer to the boundaries of protected areas with livestock predation being the most prevalent form of conflict. The type and severity of the conflict is largely dependent on the predator involved and the efficiency of the mitigation techniques employed. In an attempt to minimise human-wildlife interactions, many countries have set aside pieces of land for biodiversity conservation and management of wildlife species. However, the majority of these protected areas are too small to meet the ecological requirements of resident medium-large predator species. This results in some species dispersing into the neighbouring unprotected land where they come into contact with domestic animals, killing them and sometimes causing injuries. These livestock attacks ultimately trigger indiscriminate killing of predators that is fuelled by economic losses that are accrued through livestock predation and communities‟ I ABSTRACT Human-wildlife conflict continues to grow as a concern across the world. The conflict is experienced in many different forms and it has become persistent on the pastoral lands that are situated closer to the boundaries of protected areas with livestock predation being the most prevalent form of conflict. The type and severity of the conflict is largely dependent on the predator involved and the efficiency of the mitigation techniques employed. In an attempt to minimise human-wildlife interactions, many countries have set aside pieces of land for biodiversity conservation and management of wildlife species. However, the majority of these protected areas are too small to meet the ecological requirements of resident medium-large predator species. This results in some species dispersing into the neighbouring unprotected land where they come into contact with domestic animals, killing them and sometimes causing injuries. These livestock attacks ultimately trigger indiscriminate killing of predators that is fuelled by economic losses that are accrued through livestock predation and communities‟ negative perceptions towards predators. Camera trapping and spoor count techniques were used to study the occupancy of medium-large predator species and their movement in and out of Jwana Game Park through the holes that occur under the park‟s perimeter fence. In addition, a questionnaire survey was conducted in the cattle posts that are situated adjacent to Jwana Game Park. Seven medium-large predator species were detected within the boundaries of the park. Occupancy estimates varied among the predator species within the different sections of the game park. Predators also exhibited movement between the park and adjacent pastoral land using holes that occurred under the park‟s boundary fence. A total of 128 active holes were recorded under the park‟s perimeter fence with the majority (62%) of the intensively used holes occurring in the south-west section of the park. A total of 185 predator images were recorded at the various holes under the boundary fence with black-backed jackal (Canis mesomelas) constituting the majority (45%) of capture events. Human wildlife conflict is common on the neighbouring farmlands and jackal was perceived to be responsible for the majority of the livestock depredation incidents of small stock (mainly goats), whereas leopard was perceived as the most problematic predator species on the commercial cattle ranches where it accounted for 63% of livestock losses. There was no association between the occupancy of predators inside the park and the use of holes that occur under the park‟s the boundary fence. Conflict mitigation techniques were not efficiently practiced by communities farming in the vicinity of the game park, which potentially contributed to increased livestock attacks. The incapability of the boundary fence to restrict animal movement could also contribute to increased unwanted predator-livestock interactions. / College of Agriculture and Environmental Sciences / M. Sc. (Environmental Science)

This diploma thesis focuses on a design of camera control system used for detecting defects, appearing during a UV luminescent glue application on the bottom of a paper bag. As a part of this thesis, an application was developed, using Baumer VCXG-53C industrial camera, implementing two dierent control methods - 2D cross correlation image pattern matching based on previously user defined pattern and glue area size measuring based on binary segmented image. The result of this work is a fully developed control system, prepared to be put into operation at the customer’s production line.

Master's thesis deals with the design, assembly, and testing of a camera system for localization of randomly placed and oriented objects on a conveyor belt with the purpose of guiding a robot on those objects. The theoretical part is focused on research in individual components making a camera system and on the field of 2D and 3D localization of objects. The practical part consists of two possible arrangements of the camera system, solution of the chosen arrangement, creating testing images, programming the algorithm for image processing, creating HMI, and testing the complete system.

This diploma thesis deals with the design and implementation of appropriate procedure photogrammetry processing of technical documentation of selected historical artifacts gauges. During processing was calibrated camera, historical gauges were photographed and metrological documented and model viualization was created.

his Diploma thesis deals with non-contact measurement of surface temperatures. Describes the basic physical principles by which individual instruments are designed, their technical parameters and compares the different types. It deals with the applications of this technology in various fields of human activity and especially its use in engineering.

The subject of this master's thesis was to get familiar with a robot developed at the Department of Intelligent Systems of FIT VUT Brno. The goal of this work was to design and then implement hardware and software improvements of the robot so it could be capable of telepresence exploration of a narrow cave using remote control, including autonomous return back to the entrance. Also suggest possible extensions for a further improvement of the robot.

This thesis describes design and practical realization of a golf simulator. It includes specifications of the hardware, that is a necessity for such simulator, and implementation of the detection of a golf swing and ball flight. The simulator has to fulfill several conditions that were stated at the beginning of the draft. One of the most important conditions was low purchase price, and therefore the simulator is based on common USB cameras Playstation Eye 3. The main goal was to create a user friendly simulator, that will be appropriate both for indoor and outdoor conditions. The final solution was compared with Full Swing simulator. The accuracy of our simulator was far better than the compared one at short game and putting through the use of scanning the ball right after the start of its flight. Accuracy at putting ranged: speed of the ball +/- 0.2 m/s, launch angle +/- 1 degree and flight angle +/- 0.8 degrees.