A frontal view gait recognition based on 3D imaging using a time of flight camera

Studies have been carried out to recognize individuals from a frontal view using their gait patterns. In previous work, gait sequences were captured using either single or stereo RGB camera systems or the Kinect 1.0 camera system. In this research, we used a new frontal view gait recognition method using a laser based Time of Flight (ToF) camera. In addition to the new gait data set, other contributions include enhancement of the silhouette segmentation, gait cycle estimation and gait image representations. We propose four new gait image representations namely Gait Depth Energy Image (GDE), Partial GDE (PGDE), Discrete Cosine Transform GDE (DGDE) and Partial DGDE (PDGDE). The experimental results show that all the proposed gait image representations produce better accuracy than the previous methods. In addition, we have also developed Fusion GDEs (FGDEs) which achieve better overall accuracy and outperform the previous methods.

k-fold Subsampling based Sequential Backward Feature Elimination

We present a new wrapper feature selection algorithm for human detection. This algorithm is a hybrid featureselection approach combining the benefits of filter and wrapper methods. It allows the selection of an optimalfeature vector that well represents the shapes of the subjects in the images. In detail, the proposed featureselection algorithm adopts the k-fold subsampling and sequential backward elimination approach, while thestandard linear support vector machine (SVM) is used as the classifier for human detection. We apply theproposed algorithm to the publicly accessible INRIA and ETH pedestrian full image datasets with the PASCALVOC evaluation criteria. Compared to other state of the arts algorithms, our feature selection based approachcan improve the detection speed of the SVM classifier by over 50% with up to 2% better detection accuracy.Our algorithm also outperforms the equivalent systems introduced in the deformable part model approach witharound 9% improvement in the detection accuracy

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies

Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost.

Stakeholders based branding : uma abordagem integradora dos actores locais na gestão de marcas territoriais

O presente trabalho situa a investigação em torno do marketing, particularmente do branding, territorial numa perspectiva holística e consubstanciadora de comportamentos, identidade e desenvolvimento territorial. Nesse âmbito, focaliza-se na problemática da amplitude e heterogeneidade de actores com capacidade de impacte na construção e transmissão da marca territorial e na necessidade da sua contemplação nos pressupostos de branding para a sustentação efectiva das marcas territoriais. A tese defendida advoga a relevância de empreender marcas territoriais assentes na colaboração e integração dos stakeholders no processo construtivo, de forma a potenciar a relação directa entre o branding, a identidade e comportamento territorial e aumentar o output da marca. Nesse sentido, essa orientação é consubstanciada sob a edificação conceptual de Stakeholders Based Branding e procede-se à exploração e aferição de contributos para o seu desenvolvimento e modelização. Empiricamente e tendo por base uma abordagem descritiva e exploratória, a investigação orienta-se a um trabalho de natureza qualitativa e interpretativa que estuda, neste âmbito e através da metodologia de Grounded Theory, 6 casos de estudo de municípios portugueses, através de 48 entrevistas em profundidade realizadas a líderes políticos e stakeholders territoriais e dados secundários. Os resultados obtidos em campo demonstram a relação entre a integração de stakeholders e o sentimento de branding e imagem territorial, reiterando que quanto mais envolvidos os stakeholders se sentem no processo construtivo da marca territorial, mais tendem a assumir a sua auto-imputação e que os territórios com posturas mais colaborativas na construção de branding são os que tendem a possuir auto-imagens e imagens públicas mais positivas. Paralelamente permitem aferir um conjunto de factores impulsores, implementados e/ou idealizados, tidos como relevantes para promover uma orientação de Stakeholders Based Branding, nos respectivos territórios. Do percurso investigativo emana um constructo de Stakeholders Based Branding, com carácter indutivo, respeitando os pressupostos da Grounded Theory e assente na modelização e constituição de proposições teóricas que visam contribuir para orientar a construção de marcas territoriais alicerçadas na integração e colaboração de stakeholders.

Subspace-based techniques and applications

Este trabalho focou-se no estudo de técnicas de sub-espaço tendo em vista as aplicações seguintes: eliminação de ruído em séries temporais e extracção de características para problemas de classificação supervisionada. Foram estudadas as vertentes lineares e não-lineares das referidas técnicas tendo como ponto de partida os algoritmos SSA e KPCA. No trabalho apresentam-se propostas para optimizar os algoritmos, bem como uma descrição dos mesmos numa abordagem diferente daquela que é feita na literatura. Em qualquer das vertentes, linear ou não-linear, os métodos são apresentados utilizando uma formulação algébrica consistente. O modelo de subespaço é obtido calculando a decomposição em valores e vectores próprios das matrizes de kernel ou de correlação/covariância calculadas com um conjunto de dados multidimensional. A complexidade das técnicas não lineares de subespaço é discutida, nomeadamente, o problema da pre-imagem e a decomposição em valores e vectores próprios de matrizes de dimensão elevada. Diferentes algoritmos de préimagem são apresentados bem como propostas alternativas para a sua optimização. A decomposição em vectores próprios da matriz de kernel baseada em aproximações low-rank da matriz conduz a um algoritmo mais eficiente- o Greedy KPCA. Os algoritmos são aplicados a sinais artificiais de modo a estudar a influência dos vários parâmetros na sua performance. Para além disso, a exploração destas técnicas é extendida à eliminação de artefactos em séries temporais biomédicas univariáveis, nomeadamente, sinais EEG.

MPGDs based radiation imaging devices and applications

Este trabalho descreve o desenvolvimento e aplicação de sistemas baseados em detetores gasosos microestruturados, para imagiologia de fluorescência de raios-X por dispersão em energia (EDXRF). A técnica de imagiologia por fluorescência de raios-X assume-se como uma técnica poderosa, não-destrutiva, em análises da distribuição espacial de elementos em materiais. Os sistemas para imagiologia de EDXRF desenvolvidos são constituídos por: um tubo de raios-X, usado para excitar os elementos da amostra; um detetor gasoso microestruturado; e uma lente pinhole que foca a radiação de fluorescência no plano do detetor formando assim a imagem e permitindo a sua ampliação. Por outro lado é estudada a influência do diâmetro da abertura do pinhole bem como do fator de ampliação obtido para a imagem, na resolução em posição do sistema. Foram usados dois conceitos diferentes de detetores gasosos microestruturados. O primeiro, baseado na microestrutura designada por 2D-Micro-Hole & Strip Plate (2D-MHSP) com uma área ativa de 3 3 cm2, enquanto que o segundo, baseado na estrutura 2D-Thick-COBRA (2D-THCOBRA) apresenta uma área ativa de deteção de 10 10 cm2. Estes detetores de raios-X de baixo custo têm a particularidade de funcionar em regime de fotão único permitindo a determinação da energia e posição de interação de cada fotão que chega ao detetor. Deste modo permitem detetar a energia dos fotões X de fluorescência, bem como obter imagens 2D da distribuição desses fotões X para o intervalo de energias desejado. São por isso adequados a aplicações de imagiologia de EDXRF. Os detetores desenvolvidos mostraram resoluções em energia de 17% e 22% para fotões incidentes com uma energia de 5.9 keV, respectivamente para o detetor 2D-MHSP e 2D-THCOBRA e resoluções em posição adequadas para um vasto número de aplicações. Ao longo deste trabalho é detalhado o desenvolvimento, o estudo das características e do desempenho de cada um dos detetores, e sua influência na performance final de cada sistema proposto. Numa fase mais avançada apresentam-se os resultados correspondentes à aplicação dos dois sistemas a diversas amostras, incluindo algumas do nosso património cultural e também uma amostra biológica.

Revival: The Aesthetics of Revival Subcultures and Re-enactment Groups Explored Through Fashion Image-making

This research aims, through performance, fashion photography, video making and the theatrical devices that accompany such practice, to explore the style of a contemporary, largely male, subcultural collective. The common term that joins these loosely bound groups is revival as they appear driven by an impulse to simulate and re-enact the dress, rites and rituals of British and American subcultures from a perceived golden era. The similarities with re-enactment societies are also explored and exploited to the end of developing new style- based aesthetics in male fashion image-making formed around an elaborate re- enactment of Spartacus and the Third Servile Wars. Examined through comparative visuals (revivalists / re-enactors) a common thread is found in the wearing of leather as a metaphor for resistance, style and a pupa-like second skin. Subsequent findings of this research suggest that the cuirass of popular culture emerges as the motorcycle jacket of both the sword and sandal epic and the historical re-enactor. Addressing extremes in narcissistic dress and behaviour amongst certain individuals within these older male communities, this study also questions parts of established theory on subcultural development within the field of cultural studies and postulates on a metaphorical dandy gene. Citing two leading practitioners in the field of fashion photography the work of both Richard Prince and Bruce Weber is viewed through the lens of the subcultural aesthete and conclusions drawn as to their role as agents provocateurs in the development of the fashion image with a revival based narrative. In addition the often used term retro is examined, categorised and granted its own genre within fashion image- making and defined as being separate from the practice element of this research. Reflecting a multi-disciplinary approach that engages the researcher as Bricoleur and participant observer this research operates in the reflexive realm and uses simulation as a key method of enquiry. The practice-led outcome of this investigation takes the form of a final research exhibition that takes the form of a substantial installation of photography, video, clothing and textile prints. Key terms: dandy gene, historical re-enactment groups, internal theatre, narcissism, narrative image-making, reflexive practice, revival as theatre, subcultures,

Adaptive self-calibrating image rejection receiver

An adaptive self-calibrating image rejection receiver is described, containing a modified Weaver image rejection mixer and a Digital Image Rejection Processor (DIRP). The blind source-separation-based DIRP eliminates the I/Q errors improving the Image Rejection Ratio (IRR) without the need for trimming or use of power-hungry discrete components. Hardware complexity is minimal, requiring only two complex coefficients; hence it can be easily integrated into the signal processing path of any receiver. Simulation results show that the proposed approach achieves 75-97 dB of IRR.

Design and low-power implementation of an adaptive image rejection receiver

This paper deals with and details the design and implementation of a low-power; hardware-efficient adaptive self-calibrating image rejection receiver based on blind-source-separation that alleviates the RF analog front-end impairments. Hybrid strength-reduced and re-scheduled data-flow, low-power implementation of the adaptive self-calibration algorithm is developed and its efficiency is demonstrated through simulation case studies. A behavioral and structural model is developed in Matlab as well as a low-level architectural design in VHDL providing valuable test benches for the performance measures undertaken on the detailed algorithms and structures.

Design of a power-aware digital image rejection receiver

This paper deals with and details the design of a power-aware adaptive digital image rejection receiver based on blind-source-separation that alleviates the RF analog front-end impairments. Power-aware system design at the RTL level without having to redesign arithmetic circuits is used to reduce the power consumption in nomadic devices. Power-aware multipliers with configurable precision are used to trade-off the image-rejection-ratio (IRR) performance with power consumption. Results of the simulation case studies demonstrate that the IRR performance of the power-aware system is comparable to that of the normal implementation albeit degraded slightly, but well within the acceptable limits.

Image, video and 3D data registration: medical, satellite and video processing applications with quality metrics

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods. This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state–of–the–art registration methodologies used in a variety of targeted applications.

Example-Based Face Shape Recovery Using the Zenith Angle of the Surface Normal

We present a method for recovering facial shape using an image of a face and a reference model. The zenith angle of the surface normal is recovered directly from the intensities of the image. The azimuth angle of the reference model is then combined with the calculated zenith angle in order to get a new field of surface normals. After integration of the needle map, the recovered surface has the effect of mapped facial features over the reference model. Experiments demonstrate that for the lambertian case, surface recovery is achieved with high accuracy. For non-Lambertian cases, experiments suggest potential for face recognition applications.

FPGA-based architecture for hyperspectral unmixing

This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.

Decentralized Target Tracking based on Multi-Robot Cooperative Triangulation

Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.