This thesis is about the development of the MARS camera: a standalone portable digital x-ray camera with spectral sensitivity. It is built for use in the MARS Spectral system from the Medipix2 and Medipix3 imaging chips. Photon counting detectors and Spectral CT are introduced, and Medipix is identified as a powerful new imaging device. The goals and strategy for the MARS camera are discussed. The Medipix chip physical, electronic and functional aspects, and experience gained, are described. The camera hardware, firmware and supporting PC software are presented. Reports of experimental work on the process of equalisation from noise, and of tests of charge summing mode, conclude the main body of the thesis. The camera has been actively used since late 2009 in pre-clinical research. A list of publications that derive from the use of the camera and the MARS Spectral scanner demonstrates the practical benefits already obtained from this work. Two of the publications are first-author, eight are co-authored, and a further four acknowledge use of the MARS camera as part of the MARS scanner. The work has been presented at three MARS group meetings, two departmental conferences, and at an internal Medipix3 collaboration meeting hosted by ESRF in Grenoble.

This thesis characterizes the problem of relative camera calibration in the context of three-dimensional volumetric reconstruction. The general effects of camera calibration errors on different parameters of the projection matrix are well understood. In addition, calibration error and Euclidean world errors for a single camera can be related via the inverse perspective projection. However, there has been little analysis of camera calibration for a large number of views and how those errors directly influence the accuracy of recovered three-dimensional models. A specific analysis of how camera calibration error is propagated to reconstruction errors using traditional voxel coloring algorithms is discussed. A review of the Voxel coloring algorithm is included and the general methods applied in the coloring algorithm are related to camera error. In addition, a specific, but common, experimental setup used to acquire real-world objects through voxel coloring is introduced. Methods for relative calibration for this specific setup are discussed as well as a method to measure calibration error. An analysis of effect of these errors on voxel coloring is presented, as well as a discussion concerning the effects of the resulting world-space error.

With the proliferation of cameras and advanced video analytics, situation awareness applications that automatically generate actionable knowledge from live camera streams has become an important class of applications in various domains including surveillance, marketing, sports, health care, and traffic monitoring. However, despite the wide range of use cases, developing those applications on large-scale camera networks is extremely challenging because it involves both compute- and data-intensive workloads, has latency-sensitive quality of service requirement, and deals with inherent dynamism (e.g., number of faces detected in a certain area) from the real world. To support developing large-scale situation awareness applications, this dissertation presents a distributed framework that makes two key contributions: 1) it provides a programming model that ensures scalability of applications and 2) it supports low-latency computation and dynamic workload handling through opportunistic event processing and workload distribution over different locations and network hierarchy. To provide a scalable programming model, two programming abstractions for different levels of application logic are proposed: the first abstraction at the level of real-time target detection and tracking, and the second abstraction for answering spatio-temporal queries at a higher level. The first programming abstraction, Target Container (TC), elevates target as a first-class citizen, allowing domain experts to simply provide handlers for detection, tracking, and comparison of targets. With those handlers, TC runtime system performs priority-aware scheduling to ensure real-time tracking of important targets when resources are not enough to track all targets. The second abstraction, Spatio-temporal Analysis (STA) supports applications to answer queries related to space, time, and occupants using a global state transition table and probabilistic events. To ensure scalability, STA supports bounded communication overhead of state update by providing tuning parameters for the information propagation among distributed workers. The second part of this work explores two optimization strategies that reduce latency for stream processing and handle dynamic workload. The first strategy, an opportunistic event processing mechanism, performs event processing on predicted locations to provide just-in-time situational information to mobile users. Since location prediction algorithms are inherently inaccurate, the system selects multiple regions using a greedy algorithm to provide highly meaningful information at the given amount of computing resources. The second strategy is to distribute application workload over computing resources that are placed at different locations and various levels of network hierarchy. To support this strategy, the framework provides hierarchical communication primitives and a decentralized resource discovery protocol that allow scalable and highly adaptive load balancing over space and time.

In this thesis, an innovative algorithm for improving the accuracy of variational space-time stereoscopic reconstruction of ocean surfaces is presented. The space-time reconstruction method, developed based on stereo computer vision principles and variational optimization theory, takes videos captured by synchronized cameras as inputs and produces the shape and superficial pattern of an overlapped region of interest as outputs. These outputs are designed to be the minimizers of the variational optimization framework and are dependent on the estimation of the camera parameters. Therefore, from the perspective of computer vision, the proposed algorithm adjusts the estimation of camera parameters to lower the disagreement between the reconstruction and 2-D camera recordings. From a mathematical perspective, since the minimizers of the variational framework are determined by a set of partial differential equations (PDEs), the algorithm modifies the coefficients of the PDEs based on the current numerical solutions to reduce the minimum of the optimization framework. Our algorithm increases the tolerance to the errors of camera parameters, so the joint operations of our algorithm and the variational reconstruction method can generate accurate space-time models even using videos captured by perturbed cameras as input. This breakthrough prompts the realization of ocean surface reconstruction using videos filmed by remotely-controlled helicopters in the future. A number of techniques, technical or theoretical, are explored to fulfill the development and implementation of the algorithm and relative computation issues. The effectiveness of the proposed algorithm is validated through the statistics applied to real ocean surface reconstructions of data collected from an offshore platform at the Crimean Peninsula, the Black Sea. Moreover, synthetic data generated using computer graphics are customized to simulate various situations that are not recorded in the Crimea dataset for the demonstration of the algorithm.

Šiame darbe dėmesys sutelkiamas į dviejų mąstytojų, atstovaujančių moderniąją ir fenomenologinę tradiciją – Rene Descartes’o ir Maurice’o Merleau-Ponty – regėjimo sampratų analizę. Kaip pagrindinis darbo metodinis įrankis pasirenkama okuliarcentrizmo ir antiokuliarcentrizmo diskursų perskyra, kurią įveda šiuolaikinio vizualinio diskurso teoretikas Martinas Jay. Tokiu principu rašto darbe iškeliama ir analizuojama okuliarcentrizmo kaip epistemologinio regėjimo privilegijavimo problema, kurios ištakos siekia Platono filosofiją. Regėjimo kaip intelektinės veiklos, kontempliuojančios teorinės žiūros ar idealaus/iškūnyto žvilgsnio samprata išryškėja Platono filosofijoje, kuomet pabrėžiama juslinio pasaulio ir idėjų pasaulio bei juslinės akies ir proto akies skirtis, iškeliant pastarosios prioritetą bei nuvertinant pirmąją. Darbe parodoma, jog Descartes’as radikalizuoja šias perskyras, sąmonės/kūno bei sąmonės/pasaulio dualizmo pagrindu, įtvirtindamas regėjimo į sąmonę redukciją. Šioms skirtims eksplikuoti remiamasi Descartes’o regėjimo modelio kaip cameros obscuros, karteziškojo perspektyvizmo ir negyvos akies identifikacijomis. Iškeltos problemos pagrindu darbe suformuluojama tezė, kad Merleau-Ponty vykdoma karteziškosios regėjimo sampratos transformacija yra okuliarcentrizmo kaip sąmonės/kūno ir sąmonės/pasaulio dualizmo problemos įveika. Tvirtinama, jog Merleau-Ponty įveikia sąmonės/kūno ir sąmonės/pasaulio perskyras, formuluodamas regėjimo kaip komunikacijos, įkūnytos... [toliau žr. visą tekstą] / The work focuses on the analysis of the visual conception of the two thinkers – Rene Descartes and Maurice Merleau-Ponty – who are representing modern and fenomenological traditions. As a main methodological tool is chosen the typology of the discourses of ocularcentrism and antiocularcentrism, which are introduced by the contemporary visual theorist Martin Jay. Thus the problem of ocularcentrism is raised and analyzed as a problem of the epistemological privilegiation of the visual, which origins are found in Plato’s philosophy. The conception of the visual as an intellectual act, contemplative theoretical gaze or ideal/disembodied vision is emphasized in the philosophy of Plato, where he distinguishes the sensual world and the world of ideas, the sensual eye and the eye of mind, raising the priority for the latter and devaluating the previous one. The paper shows Descartes to radicalize those distinctions on the basis of the dualism of consciousness/body and consciousness/world, establishing reduction of the vision into the consciousness. To explicate that, it is refered to the visual Descartes’ model as identifications of camera obscura, Cartesian perspectivalism and dead eye. On the basis of the arised problem the thesis of the paper is being formulated: transformation of the Cartesian visual conception made by Merleau-Ponty is the solution of ocularcentrism as the problem of consciousness/body and consciousness/world dualism. It is stated that Merleau-Ponty resolves the... [to full text]

In social scenes, humans interact with each other by sending visible social signals, such as facial expressions, body gestures, and gaze movements. Social cognition, the ability to perceive, model, and predict such social signals, enables people to understand social interactions and to plan their behavior in accordance with the understanding. Computational social cognition is a necessary function allowing artificial agents to enter the social spaces because it enables a socially acceptable behavior. However, two key challenges preclude developing computational social cognition: (1) the core attributes of social cognition such as attention, emotion, and intent are latent quantities that cannot be directly measured by existing sensors; (2) social behaviors are interdependent to each other, i.e., a unified representation is required to understand social behavior as wholes. In this thesis, we address these challenges by establishing a computational foundation towards social scene understanding from social cameras. A social camera is a camera held or worn by a member of a social group that inherits his/her gaze behavior. This social camera is an ideal sensor to capture social signals for three reasons: (1) social cameras naturally secure the best view because the wearers or holders intelligently localize the best view point to attend to what they find interesting; (2) social cameras produce more views of events of greater interest; (3) social cameras efficiently capture socially important events by following social behaviors when the scenes are dynamic. We leverage these advantages of social cameras to understand social scenes. We present a framework to develop social cognition by perceiving social signals, modeling the relationship between them, and predicting social behaviors. Social Signal Reconstruction: Reconstructing social signals in a unified 3D coordinate system provides a computational basis to analyze social scenes, e.g., to build a model, reason about relationships, and predict social behaviors. We leverage social cameras to reconstruct three types of social signals: gaze movement, body motion, and general scene motion. (1) Gaze is a strong indicator of attentive behaviors. We model the gaze using the primary gaze direction that is emitted from the center of the eyes and aligned with the head orientation. This gaze model is reconstructed in 3D by leveraging ego- and exo-motion of social cameras. (2) Human body motion such as gestures often conveys intent of social interactions. We model skeletal motion using a set of articulated joint trajectories where the distance between the trajectories of adjacent joints remains constant. This articulation constraint in conjunction with a temporal constraint is applied to reconstruct human body motion without an activity specific prior. (3)We further relax the articulation constraint to model general scene motion occurring in social interactions. We represent a 3D trajectory using a linear combination of predefined trajectory basis vectors. We solve for the parameters of each trajectory by formulating it as a linear least squares system that allows us to reconstruct topology-independent motion and handle missing data. Social Behavior Understanding: Social behaviors are interactive by definition and therefore, an individual behavioral analysis in isolation cannot fully account for the fundamental relationship between behaviors. For instance, a social signal transmitted by one person can trigger responses in other and the responses can, in turn, affect the behavior of the person. A relational analysis between the signals is needed to characterize the social interactions. We exploit the reconstructed social signals in a unified coordinate system to understand the relationship between them. In particular, our analysis focuses on joint attention, the primary social attribute that is strongly corv related with attentive behaviors. We present a method to reconstruct 3D joint attention modeled by social charges—latent quantities that form at locations where primary gaze directions of members in a social group intersect. Inspired by the study of electric fields, we model the relationship between gaze behaviors using a gradient field induced by the social charges. This gradient field allows us to predict gaze behaviors given social charges at any location in the scene. Our overarching goal is to develop computational social cognition that will enable artificial agents to accomplish their tasks in a socially acceptable way. This thesis takes a first step towards the goal by leveraging social cameras. We present a 3D representation of social signals and based on the reconstructed signals, we build a relational model of social behaviors, which allows us to predict the behaviors. We apply our frameworks in real-world social scenes including sporting events, meetings, and parties.

There are several potential applications for a high data density barcode that can be easily photographed and decoded by mobile phones, but no such symbology currently exists. As a result, a new barcode was designed to exploit the low-pass characteristic of a camera phone channel and is presented as a means of facilitating wireless optical communication with mobile phones. A channel model was established and subsequent simulation results led to the design of a colour barcode with encoding done in the Discrete Cosine Transform domain. A waterfilling process and a noise-shaping algorithm enhance performance, while a new fast acquisition method allows for rotational and size invariance. An outer Accumulate-Repeat-Accumulate code is employed, followed by an inner Reed Muller code with a rate varying according to spatial frequency. The final barcode data-density is 3.5 times greater than the leading symbology and has proven robust to various impediments imposed by camera phones.

There are several potential applications for a high data density barcode that can be easily photographed and decoded by mobile phones, but no such symbology currently exists. As a result, a new barcode was designed to exploit the low-pass characteristic of a camera phone channel and is presented as a means of facilitating wireless optical communication with mobile phones. A channel model was established and subsequent simulation results led to the design of a colour barcode with encoding done in the Discrete Cosine Transform domain. A waterfilling process and a noise-shaping algorithm enhance performance, while a new fast acquisition method allows for rotational and size invariance. An outer Accumulate-Repeat-Accumulate code is employed, followed by an inner Reed Muller code with a rate varying according to spatial frequency. The final barcode data-density is 3.5 times greater than the leading symbology and has proven robust to various impediments imposed by camera phones.

The main aim of this thesis is to generate 3D models of human heads from uncalibrated images. In order to extract geometric values of a human head, we find camera parameters using camera auto calibration. However, some image sequences generate non-unique (degenerate) solutions. An algorithm for removing degeneracy from the most common form of camera movement in face image acquisition is described. The geometric values of main facial features are computed initially. The model is then generated by gradual deformation of a generic polygonal model of a head. The accuracy of the models is evaluated using ground truth data from a range scanner. 3D models are covered with cylindrical texture values obtained from images. The models are appropriate for animation or identification applications.

This study examines some of the fundamental principles of a number of influential photographers working in Germany in the 1920s and assesses the ways they understood the world through their camera's lens. German photography initiated a complex engagement with the modern world and marked a significant reevaluation of the relationship between the camera, perception and reality. The unique quality of the photographic image's verisimilitude of nature was an important phenomenon in this re-evaluation, as it led to assumptions about the capacity of photography to reveal the truth of reality. László Moholy-Nagy's innovative employment of a variety of photographic techniques provide an effective conduit to modern theories about photography that not only expose the presumptions surrounding the photographic image, but also the inherent complications. I propose that the avant-garde photographic experiments of 1920s Germany radically changed the ways in which humanity perceived and interacted with the surrounding world.