A swarm intelligence method for feature tracking in AMV derivation

Feature tracking is a key step in the derivation of Atmospheric Motion Vectors (AMV). Most operational derivation processes use some template matching technique, such as Euclidean distance or cross-correlation, for the tracking step. As this step is very expensive computationally, often shortrange forecasts generated by Numerical Weather Prediction (NWP) systems are used to reduce the search area. Alternatives, such as optical flow methods, have been explored, with the aim of improving the number and quality of the vectors generated and the computational efficiency of the process. This paper will present the research carried out to apply Stochastic Diffusion Search, a generic search technique in the Swarm Intelligence family, to feature tracking in the context of AMV derivation. The method will be described, and we will present initial results, with Euclidean distance as reference.

Application of Gaussian multi-scale representation to feature tracking in meteorological satellite imagery

Gaussian multi-scale representation is a mathematical framework that allows to analyse images at different scales in a consistent manner, and to handle derivatives in a way deeply connected to scale. This paper uses Gaussian multi-scale representation to investigate several aspects of the derivation of atmospheric motion vectors (AMVs) from water vapour imagery. The contribution of different spatial frequencies to the tracking is studied, for a range of tracer sizes, and a number of tracer selection methods are presented and compared, using WV 6.2 images from the geostationary satellite MSG-2.

Untersuchungen zum Sehen von bewegten Objekten beim Goldfisch (Carassius auratus)

In der vorliegenden Arbeit wurde das Objektbewegungssehen des Goldfischs betrachtet. Zuerst musste eine geeignete Methode gefunden werden, diese Form der Bewegungswahrnehmung untersuchen zu können, da bisherige Experimente zum Bewegungssehen beim Goldfisch ausschließlich mit Hilfe der optomotorischen Folgereaktion gemacht wurden. Anschließend sollte die Frage geklärt werden, ob das Objektbewegungssehen genau wie das Bewegungssehen einer Großfeldbewegung farbenblind ist und welcher Zapfentyp daran beteiligt ist. Die Verwendung eines Zufallpunktmusters zur Dressur auf ein bewegtes Objekt hat sich als äußert erfolgreich herausgestellt. Diese Methode hat den Vorteil, dass sich die Versuchstiere ausschließlich aufgrund der Bewegungsinformation orientieren können. In den Rot-Grün- und Blau-Grün-Transferversuchen zeigte sich, dass das Objektbewegungssehen beim Goldfisch farbenblind ist, aber erstaunlicherweise nicht vom L-Zapfen vermittelt wird, sondern wahrscheinlich vom M-Zapfen. Welchen Vorteil es haben könnte, dass für die verschiedenen Formen der Bewegungswahrnehmung verschiedene Eingänge benutzt werden, kann mit diesen Versuchen nicht geklärt werden. Farbenblindheit des Bewegungssehens scheint eine Eigenschaft visueller Systeme allgemein zu sein. Beim Menschen ist diese Frage im Moment noch nicht geklärt und wird weiterhin diskutiert, da es sowohl Experimente gibt, die zeigen, dass es farbenblind ist, als auch andere, die Hinweise darauf geben, dass es nicht farbenblind ist. Der Vorteil der Farbenblindheit eines bewegungsdetektierenden visuellen Systems zeigt sich auch in der Technik beim Maschinen Sehen. Hier wird ebenfalls auf Farbinformation verzichtet, was zum einen eine Datenreduktion mit sich bringt und zum anderen dazu führt, dass korrespondierende Bildpunkte leichter gefunden werden können. Diese werden benötigt, um Bewegungsvektoren zu bestimmen und letztlich Bewegung zu detektieren.

Relating Crevassing to Non-Linear Strain in the Floating Part of Jakobshavn Isbrae, West Greenland

Jakobshavn Isbrae is a major ice stream that drains the west-central Greenland ice sheet and becomes afloat in Jakobshavn Isfiord (69degreesN, 49degreesW), where it has maintained the world's fastest-known sustained velocity and calving rate (7 km a(-1)) for at least four decades. The floating portion is approximately 12 km long and 6 km wide. Surface elevations and motion vectors were determined photogrammetrically for about 500 crevasses on the floating ice, and adjacent grounded ice, using aerial photographs obtained 2 weeks apart in July 1985. Surface strain rates were computed from a mesh of 399 quadrilateral elements having velocity measurements at each corner. It is shown that heavy crevassing of floating ice invalidates the assumptions of linear strain theory that (i) surface strain in the floating ice is homogeneous in both space and time, (ii) the squares and products of strain components are nil, and (iii) first- and second-order rotation components are small compared to strain components. Therefore, strain rates and rotation rates were also computed using non-linear strain theory. The percentage difference between computed linear and non-linear second invariants of strain rate per element were greatest (mostly in the range 40-70%) where crevassing is greatest. Isopleths of strain rate parallel and transverse to flow and elevation isopleths relate crevassing to known and inferred pinning points.

Análisis de imágenes basado en correlación de imágenes

El objetivo principal del proyecto es la realización de una aplicación en el programa MATLAB. En primer lugar, realizaremos un estudio teórico relativo al tema de nuestro proyecto. En nuestro caso como el tema es Imagen y Televisión, explicaremos de forma teórica la información principal acerca del Tratamiento Digital de la Imagen. Una vez conocida las técnicas principales utilizadas en el tratamiento digital, realizaremos un estudio exhaustivo en las técnicas actuales que existen acerca del análisis de imágenes. Daremos una breve explicación mostrando en qué consiste esta técnica, los diferentes pasos que se llevan a cabo en una imagen para su análisis, explicando brevemente cada unos de ellos y enumerando algunas técnicas para la realización de cada una de ellas. Tras esta primera parte, nos centraremos en las técnicas de correlación de imágenes (DIC). Explicaremos como han surgido estas técnicas, cual son sus principales conceptos, sus inicios y las ventajas e inconvenientes que tienen. Dentro de las diferentes técnicas de correlación de imágenes, explicaremos de forma detallada la correspondencia por áreas, ya que es la técnica que vamos a utilizar para la realización del proyecto. Explicaremos en qué consiste, y desarrollaremos teóricamente cual son los pasos que se deben realizar en las imágenes para realizar esta técnica. Explicaremos cual es su terminología, y cuáles son los posibles defectos que puede tener esta técnica. Finalmente, una vez estudiada la teoría, realizaremos una sencilla aplicación que nos permita evaluar y encontrar las diferencias en una secuencia de imágenes. El programa utilizado para este proyecto es MATLAB, que es un programa matemático, utilizado enormemente en el ámbito de la ingeniería. Mediante esta aplicación obtendremos dos figuras, una de ellas donde veremos los vectores de movimiento que existen entre las dos imágenes y la segunda, donde obtendremos el factor de correlación que hay entre las dos imágenes. ABSTRACT OF MY PROJECT The main objective of the project is the development of an application in MATLAB program. Firstly carry out a theoretical study on the topic of our project. In our case as the theme is Picture and Television, we explain the main information about Digital Image Processing. Once known the main techniques used in digital images, we will make a study on current techniques that exist about image analysis. We will give a brief explanation showing what this technique is, the different steps that are performed on an image for analysis, briefly explaining each of them and listing some techniques for performing each. After this first part, we will focus on the techniques of image correlation (DIC). We explain how these techniques have emerged, which are the main concepts, the beginning and the advantages and disadvantages they have. There are different image correlation techniques. We will explain in detail the correspondence areas, as it is the technique that we will use for the project. Explain what it is, which is theoretically and we develop steps that must be performed on the images for this technique. We explain what their terminology is, and what are the possible defects that may have this technique. Finally, having explored the theory images, we will make a simple application that allows us to evaluate and find differences in a sequence of images. The program used for this project is MATLAB, a mathematical program, widely used in the field of engineering. Using this application will get two figures, one where we will see the motion vectors between the two images and the second where we get the correlation factor between the two images.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

The role of the harmonic vector average in motion integration

The local speeds of object contours vary systematically with the cosine of the angle between the normal component of the local velocity and the global object motion direction. An array of Gabor elements whose speed changes with local spatial orientation in accordance with this pattern can appear to move as a single surface. The apparent direction of motion of plaids and Gabor arrays has variously been proposed to result from feature tracking, vector addition and vector averaging in addition to the geometrically correct global velocity as indicated by the intersection of constraints (IOC) solution. Here a new combination rule, the harmonic vector average (HVA), is introduced, as well as a new algorithm for computing the IOC solution. The vector sum can be discounted as an integration strategy as it increases with the number of elements. The vector average over local vectors that vary in direction always provides an underestimate of the true global speed. The HVA, however, provides the correct global speed and direction for an unbiased sample of local velocities with respect to the global motion direction, as is the case for a simple closed contour. The HVA over biased samples provides an aggregate velocity estimate that can still be combined through an IOC computation to give an accurate estimate of the global velocity, which is not true of the vector average. Psychophysical results for type II Gabor arrays show perceived direction and speed falls close to the IOC direction for Gabor arrays having a wide range of orientations but the IOC prediction fails as the mean orientation shifts away from the global motion direction and the orientation range narrows. In this case perceived velocity generally defaults to the HVA.

Estimating Gesture Accuracy in Motion-Based Health Games

This manuscript details a technique for estimating gesture accuracy within the context of motion-based health video games using the MICROSOFT KINECT. We created a physical therapy game that requires players to imitate clinically significant reference gestures. Player performance is represented by the degree of similarity between the performed and reference gestures and is quantified by collecting the Euler angles of the player's gestures, converting them to a three-dimensional vector, and comparing the magnitude between the vectors. Lower difference values represent greater gestural correspondence and therefore greater player performance. A group of thirty-one subjects was tested. Subjects achieved gestural correspondence sufficient to complete the game's objectives while also improving their ability to perform reference gestures accurately.

Feature-based tracking of urethral motion in low-resolution trans-perineal ultrasound

This paper describes a novel algorithm for tracking the motion of the urethra from trans-perineal ultrasound. Our work is based on the structure-from-motion paradigm and therefore handles well structures with ill-defined and partially missing boundaries. The proposed approach is particularly well-suited for video sequences of low resolution and variable levels of blurriness introduced by anatomical motion of variable speed. Our tracking method identifies feature points on a frame by frame basis using the SURF detector/descriptor. Inter-frame correspondence is achieved using nearest-neighbor matching in the feature space. The motion is estimated using a non-linear bi-quadratic model, which adequately describes the deformable motion of the urethra. Experimental results are promising and show that our algorithm performs well when compared to manual tracking.

Feature-based tracking of urethral motion in low-resolution trans-perineal ultrasound

This paper describes a novel algorithm for tracking the motion of the urethra from trans-perineal ultrasound. Our work is based on the structure-from-motion paradigm and therefore handles well structures with ill-defined and partially missing boundaries. The proposed approach is particularly well-suited for video sequences of low resolution and variable levels of blurriness introduced by anatomical motion of variable speed. Our tracking method identifies feature points on a frame by frame basis using the SURF detector/descriptor. Inter-frame correspondence is achieved using nearest-neighbor matching in the feature space. The motion is estimated using a non-linear bi-quadratic model, which adequately describes the deformable motion of the urethra. Experimental results are promising and show that our algorithm performs well when compared to manual tracking.

Pain Intensity And Cervical Range Of Motion In Women With Myofascial Pain Treated With Acupuncture And Electroacupuncture: A Double-blinded, Randomized Clinical Trial.

Acupuncture stimulates points on the body, influencing the perception of myofascial pain or altering physiologic functions. The aim was to evaluate the effect of electroacupuncture (EAC) and acupuncture (AC) for myofascial pain of the upper trapezius and cervical range of motion, using SHAM acupuncture as control. Sixty women presenting at least one trigger point at the upper trapezius and local or referred pain for more than six months were randomized into EAC, AC, and SHAM groups. Eight sessions were scheduled and a follow-up was conducted after 28 days. The Visual Analog Scale assessed the intensity of local and general pain. A fleximeter assessed cervical movements. Data were analyzed using paired t or Wilcoxon's tests, ANOVA or Friedman or Kruskal-Wallis tests and Pearson's correlation (α=0.05). There was reduction in general pain in the EAC and AC groups after eight sessions (P<0.001). A significant decrease in pain intensity occurred for the right trapezius in all groups and for the left trapezius in the EAC and AC groups. Intergroup comparisons showed improvement in general pain in the EAC and AC groups and in local pain intensity in the EAC group (P<0.05), which showed an increase in left rotation (P=0.049). The AC group showed increases in inclination (P=0.005) sustained until follow-up and rotation to the right (P=0.032). EAC and AC were effective in reducing the pain intensity compared with SHAM. EAC was better than AC for local pain relief. These treatments can assist in increasing cervical range of motion, albeit subtly.

Análise do desempenho muscular do quadríceps e dos isquiotibiais em função da série temporal e da amplitude de movimento de atletas amadoras de futsal feminino = : Analysis of muscle performance of the quadriceps and hamstrings as a function of the times series and range of motion of amateurfemale futsal athletes

Universidade Estadual de Campinas . Faculdade de Educação Física

Calibração de câmeras para análises subaquáticas de movimentos = : Cameras calibration for underwater motion analysis

Universidade Estadual de Campinas . Faculdade de Educação Física

Proposição de um método de análise de movimentos de jogadores de tênis de campo a partir de vídeos televisivos = : Proposition of a method for tennis players motion analysis on broadcast videos

Universidade Estadual de Campinas . Faculdade de Educação Física

Etiology of cutaneous leishmaniasis and anthropophilic vectors in Juruti, Pará State, Brazil

In a preliminary study in Juruti, a mining municipality in western Pará State, Brazil, 12 out of 21 patients suspected of presenting cutaneous leishmaniasis showed positive PCR (SSUrDNA and G6PD): Leishmania (Viannia) braziliensis (9/12; 75%) and L. (V.) sp. (3/12; 25%). Entomological studies in the same location revealed the presence of 12 different phlebotomine species (n =105). One of the most common species was Lutzomyia (Psychodopygus) complexa (17%) which is both highly anthropophilic and a known vector of L. (V.) braziliensis in other regions of Pará. These preliminary findings should serve to guide future epidemiological surveillance in Juruti.