Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering

Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image content. The performance of the proposed filter has been compared with some of the commonly used denoising filters. The proposed filter outperforms the existing filters in terms of quantitative analysis and in edge preservation. The experimental analysis is done using various ultrasound images

Transformaciones basadas en el algoritmo Local Binary Pattern de imágenes capturadas con la Kinect para clasificación facial

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Reading skills are related to global, but not local, acoustic pattern perception

Although reading ability has been related to the processing of simple pitch features such as isolated transitions or continuous modulation spoken language also contains complex patterns of pitch changes that are important for establishing stress location and for segmenting the speech stream. These aspects of spoken language processing depend critically on pitch pattern (global structure) rather than on absolute pitch values (local structure). Here we show that the detection of global structure, and not local structure, is predictive of performance on measures of phonological skill and reading ability, which supports a critical importance of pitch contour processing in the acquisition of literacy.

Human identification from video using advanced gait recognition techniques

The solutions proposed in this thesis contribute to improve gait recognition performance in practical scenarios that further enable the adoption of gait recognition into real world security and forensic applications that require identifying humans at a distance. Pioneering work has been conducted on frontal gait recognition using depth images to allow gait to be integrated with biometric walkthrough portals. The effects of gait challenging conditions including clothing, carrying goods, and viewpoint have been explored. Enhanced approaches are proposed on segmentation, feature extraction, feature optimisation and classification elements, and state-of-the-art recognition performance has been achieved. A frontal depth gait database has been developed and made available to the research community for further investigation. Solutions are explored in 2D and 3D domains using multiple images sources, and both domain-specific and independent modality gait features are proposed.

东营凹陷辛镇复杂断块油藏形成机制和剩余油分布规律研究

In this paper, the complex faulted-block oil reservoir of Xinzhen area in Dongying depression is systematically studied from basic conditions forming faulted-block oil and gas reservoir integrating geology, seismic, logging and reservoir engineering information and computer; guided by petroleum geology, geomechanics, structural geology and geophysics and other theories. Based on analysis of background condition such as regional strata, structure and petroleum geology, structural research on geometry, kinemaitcs and dynamics, oil-controlling fault research on the seal features, sealing mechanism and sealing pattern, and research on enrichment rules and controlling factors of complex faulted-block oil reservoir are carried out to give out the formation mechanics of oil reservoir of Xinzhen complex faulted-block oil reservoir. As a result, the reservoir formation pattern is established. At the same time, through dissecting the characteristics and hydrocarbon enrichment law of complex faulted-block oil reservoir, and studying its distribution law of remaining oil after entering extra high water-cut period, a set of technologies are formed to predict complex faulted-block oil reservoir and its remaining oil distribution and to enhance oil recovery (EOR). Based on the time relationship between migration of hydrocarbon and trap formation, accumulating period of Xinzhen oil reservoir is determined. The formation of Xinzhen anticlinal trap was prior to the primary migration. This is favorable to formation of Xinzhen anticlinal hydrocarbon reservoir. Meanwhile, because anticline top caving isn't at the sane time as that of moving or faulted-trap forming inner anticline, oil and gas migrated many times and Xinzhen complex faulted-block oil reservoir formed from ES_3~(upper) to EG. Accumulating law and controlling factors of complex faulted-block reservoir are analyzed from many aspects such as regional structure background controlling hydrocarbon accumulating, plastic arch-open structure controlling oil-bearing series and reservoir types, sealing-opening of fault controlling hydrocarbon distribution and structure pattern controlling enriched trap types. Also, we established the structure pattern in Xinzhen a'ea: the arch-open of underlying strata cause expanding fracture. The main block groups developed here are shovel-like normal fault block group in the north area of Xinzhen and its associated graben block group. Block groups dominate the formation and distribution of reservoirs. We studied qualitatively and quantitatively the sealing characteristics, sealing history and sealing mechanism of faults, too. And, the sealing characteristics are evaluated and the distribution pattern of hydrocarbon controlled by faults is researched. Due to movement intensity of big faults, deep falling of downthrown block, high degree of repture and development of fracture, shallow layers close to the downthrown block of secondary faults are unfavorable to hydrocarbon accumulation. This is confirmed by the exploration practice in Xinzhen anticline. In terms of the downthrown blocks of sencondary contemporaneous faults lied in the south and north area of Xinzhen, hydrocarbon is poor close to fracture belt, while it is relatively abundant in tertiary companion faults. Because of long-term movement of faults that control hydrocarbon, fi'om ES3 to EG, six set of oil-bearing series formed. And their opening causes the inhomogeneity in hydrocarbon abundance among each block--in two flanks of anticline reservoirs are abundant while in the axial area, oil and gas are sporadic. There the sealing characteristics control oil-bearing area of oil/gas accumulation and the height of oil reservoir. Longitudinally, oil and gas are enriched in dip-flat areas in mid-plane of faults. It is established that there are four types of accumulating patterns in complex faulted-block oil reservoirs in Xinzhen. The first is accumulating pattern of lithologic oil reservoirs in E~S_3~(mid-lowwer), that is, self-generating-self-reserving-self-covering lithologic trap pattern. The second is drag-anticline accumulating pattern in Xinzhen. The structure traps are drag anticlines formed by the contemporaneous faults of the second basement in the north of Xinzhen, and the multiple source rocks involve Ek_2, Es_4, Es_3 and Es_1 members. The reservoirs are fluvial-delta sandstones of the upper member of Shahejie formation and Guantao formation, covered by regional thick mudstone of the upper member of Guantao formation and MingHuazhen formation. The third is the accumulating pattern of reverse listric fault, the third-degree fault of Xinzhen anticline limb and the reservoirs form reservoir screened by reverse listric faults. The forth is accumulating pattern of crossing faults which form closing or semi-closing faulted-blocks that accumulate hydrocarbon. The technologies of predicting remaining oil in complex faulted-block reservoir during the mid and late development stage is formed. Remaining oil in simple large faulted-blocks enriches in structural high, structural middle, structural low of thick bottom water reservoirs, points near bent edge-fault oftertiary faults and part the fourth ones with big falling displacement, microstructure high place of oil-sandbodies and areas where local well pattern isn't perfect. While that in small complex faulted-blocks enriches near small nose, small high point, angle of small faults, small oil-bearing faulted-blocks without well and areas with non-perfect well pattern. The technologies of enhancing recovery factor in complex faulted-block reservoir during the mid and late development stage is formed as follows: fine reservoir description, drilling adjust wells, designing directional wells, sub-dividing layer series of development, improving flooding pattern, changing water-injection direction and enhancing swept volume, cyclic waterflooding and gas-injection, etc. Here, directional wells include directional deflecting wells, lateral-drilling wells, lateral-drilling horizontal wells and horizontal wells. The results of this paper have been used in exploration and development of Shengli oilfield, and have achieved great social and economic profit, especially in predicting distribution of complex faulted-block reservoir, remaining oil distribution during middle and late stage of development, and in EOR. Applying the achievement of fault-closure research, new hydrocarbon-bearing blocks are discovered in flanks of Dongying central uplift and in complex blocks with proved reserves 15 million tons. With the study of remaining oil distribution law in complex faulted-block reservoirs, recovery factors are increased greatly in Dongxin, Xianhe and Linpan complex faulted-block reservoirs and accumulated oil production increment is 3 million tons.

ReadingAct RGB-D action dataset and human action recognition from local features

For general home monitoring, a system should automatically interpret people’s actions. The system should be non-intrusive, and able to deal with a cluttered background, and loose clothes. An approach based on spatio-temporal local features and a Bag-of-Words (BoW) model is proposed for single-person action recognition from combined intensity and depth images. To restore the temporal structure lost in the traditional BoW method, a dynamic time alignment technique with temporal binning is applied in this work, which has not been previously implemented in the literature for human action recognition on depth imagery. A novel human action dataset with depth data has been created using two Microsoft Kinect sensors. The ReadingAct dataset contains 20 subjects and 19 actions for a total of 2340 videos. To investigate the effect of using depth images and the proposed method, testing was conducted on three depth datasets, and the proposed method was compared to traditional Bag-of-Words methods. Results showed that the proposed method improves recognition accuracy when adding depth to the conventional intensity data, and has advantages when dealing with long actions.

Depth-based face recognition using local quantized patterns adapted for range data

A depth-based face recognition algorithm specially adapted to high range resolution data acquired by the new Microsoft Kinect 2 sensor is presented. A novel descriptor called Depth Local Quantized Pattern descriptor has been designed to make use of the extended range resolution of the new sensor. This descriptor is a substantial modification of the popular Local Binary Pattern algorithm. One of the main contributions is the introduction of a quantification step, increasing its capacity to distinguish different depth patterns. The proposed descriptor has been used to train and test a Support Vector Machine classifier, which has proven to be able to accurately recognize different people faces from a wide range of poses. In addition, a new depth-based face database acquired by the new Kinect 2 sensor have been created and made public to evaluate the proposed face recognition system.

Using directional curvatures to visualize folding patterns of the GTM projection manifolds

In data visualization, characterizing local geometric properties of non-linear projection manifolds provides the user with valuable additional information that can influence further steps in the data analysis. We take advantage of the smooth character of GTM projection manifold and analytically calculate its local directional curvatures. Curvature plots are useful for detecting regions where geometry is distorted, for changing the amount of regularization in non-linear projection manifolds, and for choosing regions of interest when constructing detailed lower-level visualization plots.

Hierarchical GTM: constructing localized non-linear projection manifolds in a principled way

It has been argued that a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex data sets, and therefore a hierarchical visualization system is desirable. In this paper we extend an existing locally linear hierarchical visualization system PhiVis ¸iteBishop98a in several directions: bf(1) We allow for em non-linear projection manifolds. The basic building block is the Generative Topographic Mapping (GTM). bf(2) We introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree. General training equations are derived, regardless of the position of the model in the tree. bf(3) Using tools from differential geometry we derive expressions for local directional curvatures of the projection manifold. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. It enables the user to interactively highlight those data in the ancestor visualization plots which are captured by a child model. We also incorporate into our system a hierarchical, locally selective representation of magnification factors and directional curvatures of the projection manifolds. Such information is important for further refinement of the hierarchical visualization plot, as well as for controlling the amount of regularization imposed on the local models. We demonstrate the principle of the approach on a toy data set and apply our system to two more complex 12- and 18-dimensional data sets.

Pattern of nutrient availability and plant community assemblage in Everglades Tree Islands, Florida, USA

We address the relative importance of nutrient availability in relation to other physical and biological factors in determining plant community assemblages around Everglades Tree Islands (Everglades National Park, Florida, USA). We carried out a one-time survey of elevation, soil, water level and vegetation structure and composition at 138 plots located along transects in three tree islands in the Park’s major drainage basin. We used an RDA variance partitioning technique to assess the relative importance of nutrient availability (soil N and P) and other factors in explaining herb and tree assemblages of tree island tail and surrounded marshes. The upland areas of the tree islands accumulate P and show low N concentration, producing a strong island-wide gradient in soil N:P ratio. While soil N:P ratio plays a significant role in determining herb layer and tree layer community assemblage in tree island tails, nevertheless part of its variance is shared with hydrology. The total species variance explained by the predictors is very low. We define a strong gradient in nutrient availability (soil N:P ratio) closely related to hydrology. Hydrology and nutrient availability are both factors influencing community assemblages around tree islands, nevertheless both seem to be acting together and in a complex mechanism. Future research should be focused on segregating these two factors in order to determine whether nutrient leaching from tree islands is a factor determining community assemblages and local landscape pattern in the Everglades, and how this process might be affected by water management.

On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.

Visual detection of occluded crop: For automated harvesting

This paper presents a novel crop detection system applied to the challenging task of field sweet pepper (capsicum) detection. The field-grown sweet pepper crop presents several challenges for robotic systems such as the high degree of occlusion and the fact that the crop can have a similar colour to the background (green on green). To overcome these issues, we propose a two-stage system that performs per-pixel segmentation followed by region detection. The output of the segmentation is used to search for highly probable regions and declares these to be sweet pepper. We propose the novel use of the local binary pattern (LBP) to perform crop segmentation. This feature improves the accuracy of crop segmentation from an AUC of 0.10, for previously proposed features, to 0.56. Using the LBP feature as the basis for our two-stage algorithm, we are able to detect 69.2% of field grown sweet peppers in three sites. This is an impressive result given that the average detection accuracy of people viewing the same colour imagery is 66.8%.

El desarrollo profesional de los trabajadores como ventaja competitiva de las empresas

[ES] En este trabajo se hace una revisión de la literatura sobre el concepto de profesión y a continuación se propone un modelo de desarrollo profesional en el que se destacan los retos profesionales de los trabajadores y la posibilidad de las empresas de ayudarles a afrontarlos. También se analizan los sistemas de desarrollo profesional y los roles que en ellos juegan empleados, directores y empresas. Para finalizar, se exponen varias cuestiones de actualidad relativas al desarrollo profesional: incorporación y orientación, estabilización, obsolescencia de las habilidades, doble trayectoria profesional, conflictos trabajo-familia, pérdida del puesto de trabajo y jubilación.

Reconocimiento automático de objetos de interés in imágenes aéreas

El objetivo principal de este proyecto es la detección automática de objetos de interés en imágenes aéreas de zonas urbanas mediante el uso de descriptores característicos. Los descriptores considerados para esta tarea han sido los histogramas color y los descriptores LBP (Local Binary Pattern), así como la concatenación de ambos dando lugar a descriptores híbridos