Image segmentation and feature extraction for recognizing strokes in tennis game videos

This paper addresses the problem of recognizing human actions from video. Particularly, the case of recognizing events in tennis game videos is analyzed. Driven by our domain knowledge, a robust player segmentation algorithm is developed real video data. Further, we introduce a number of novel features to be extracted for our particular application. Different feature combinations are investigated in order to find the optimal one. Finally, recognition results for different classes of tennis strokes using automatic learning capability of Hidden Markov Models (HMMs) are presented. The experimental results demonstrate that our method is close to realizing statistics of tennis games automatically using ordinary TV broadcast videos

Background modeling for video sequences by stacked denoising autoencoders

Nowadays, the analysis and extraction of relevant information in visual data flows is of paramount importance. These images sequences can last for hours, which implies that the model must adapt to all kinds of circumstances so that the performance of the system does not decay over time. In this paper we propose a methodology for background modeling and foreground detection, whose main characteristic is its robustness against stationary noise. Thus, stacked denoising autoencoders are applied to generate a set of robust characteristics for each region or patch of the image, which will be the input of a probabilistic model to determine if that region is background or foreground. The evaluation of a set of heterogeneous sequences results in that, although our proposal is similar to the classical methods existing in the literature, the inclusion of noise in these sequences causes drastic performance drops in the competing methods, while in our case the performance stays or falls slightly.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A SIMPLE METHOD FOR ASSESSMENT OF MUSCLE MECHANICAL CAPACITIES FROM FUNCTIONAL MOVEMENT TASKS

The aim of the present study was to evaluate the level of agreement between the routinely used multiple-load method and a simple two-load method based on direct assessment of the F-V relationship from only 2 external loads applied. Twelve participants were tested on the maximum performance vertical jumps, cycling, bench press throws, and bench pull performed against a variety of different loads. All four tested tasks revealed both exceptionally strong relationships between the parameters of the 2 methods (median R = 0.98) and a lack of meaningful differences between their magnitudes (fixed bias below 3.4%). Therefore, addition of another load to the standard tests of various functional tasks typically conducted under a single set of mechanical conditions could allow for the assessment of the muscle mechanical properties, such as the muscle F, V, and P producing capacities

Factorial analysis of slaughter characteristics of fattening pigs fed different additives – Enzyme and probiotic in mixtures

To successfully investigate slaughter characteristics of fattening pigs fed in different ways, this experiment was carried out on Experimental Farm of the Institute for Animal Husbandry, Belgrade- Zemun. Investigation of correlation between slaughter traits of pigs fed with different additives in their nutrition was done by factorial analysis. Slaughter characteristics in three groups of fattening pigs fed in different ways were observed. The first group (variant 1) consisted of fatteners fed diets without any special additives. The second group (variant 2) consisted of pigs fed diets containing enzyme Rovabio, and the third group (variant 3) probiotic Lacture + Microbond. This study was aimed at coming to conclusion based on the results of factorial analysis of the observed traits to the greatest extent which determined slaughter traits of pigs fed diets containing different additives. The results obtained in general, that is, the structure of separated factors showed that different slaughter characteristics are realized with different nutrition.Key words: Fattening pigs, slaughter characteristics, enzyme Rovabio, probiotic Lacture + Microbond, factorial analysis

Real-time marker-less multi-person 3D pose estimation in RGB-Depth camera networks

This paper proposes a novel system to estimate and track the 3D poses of multiple persons in calibrated RGB-Depth camera networks. The multi-view 3D pose of each person is computed by a central node which receives the single-view outcomes from each camera of the network. Each single-view outcome is computed by using a CNN for 2D pose estimation and extending the resulting skeletons to 3D by means of the sensor depth. The proposed system is marker-less, multi-person, independent of background and does not make any assumption on people appearance and initial pose. The system provides real-time outcomes, thus being perfectly suited for applications requiring user interaction. Experimental results show the effectiveness of this work with respect to a baseline multi-view approach in different scenarios. To foster research and applications based on this work, we released the source code in OpenPTrack, an open source project for RGB-D people tracking.Comment: Submitted to the 2018 IEEE International Conference on Robotics and Automatio

Background modeling by shifted tilings of stacked denoising autoencoders

The effective processing of visual data without interruption is currently of supreme importance. For that purpose, the analysis system must adapt to events that may affect the data quality and maintain its performance level over time. A methodology for background modeling and foreground detection, whose main characteristic is its robustness against stationary noise, is presented in the paper. The system is based on a stacked denoising autoencoder which extracts a set of significant features for each patch of several shifted tilings of the video frame. A probabilistic model for each patch is learned. The distinct patches which include a particular pixel are considered for that pixel classification. The experiments show that classical methods existing in the literature experience drastic performance drops when noise is present in the video sequences, whereas the proposed one seems to be slightly affected. This fact corroborates the idea of robustness of our proposal, in addition to its usefulness for the processing and analysis of continuous data during uninterrupted periods of time.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Efficient probabilistic planar robot motion estimation given pairs of images

Estimating the relative pose between two camera positions given image point correspondences is a vital task in most view based SLAM and robot navigation approaches. In order to improve the robustness to noise and false point correspondences it is common to incorporate the constraint that the robot moves over a planar surface, as is the case for most indoor and outdoor mapping applications. We propose a novel estimation method that determines the full likelihood in the space of all possible planar relative poses. The likelihood function can be learned from existing data using standard Bayesian methods and is efficiently stored in a low dimensional look up table. Estimating the likelihood of a new pose given a set of correspondences boils down to a simple look up. As a result, the proposed method allows for very efficient creation of pose constraints for vision based SLAM applications, including a proper estimate of its uncertainty. It can handle ambiguous image data, such as acquired in long corridors, naturally. The method can be trained using either artificial or real data, and is applied on both controlled simulated data and challenging images taken in real home environments. By computing the maximum likelihood estimate we can compare our approach with state of the art estimators based on a combination of RANSAC and iterative reweighted least squares and show a significant increase in both the efficiency and accuracy

Simulation of risk based on ending activities of the design plan using special function

U radu se iznose rezultati teorijsko-eksperimentalnih istraživanja kvantifikacije superponiranog protočnog vremena dva lokalno-autonomna toka u mreži na bazi Klarkovih jednadžbi. Računarsko rješavanje ove osnovne varijante općeg modela protoka kroz mrežu izvodi se postupcima numeričke simulacije Monte-Karlo dopunjene metodom okvira. Numerički eksperiment realiziran je putem programa Mathcad Professional.In this paper are presented the results of the theoretical - experimental research on the quantification of superimposed flow time of two local - autonomous flows in a network, on the basis of Clark’s equations. The computer-based solving of this basic variant of the general flow model through the network was performed using the Monte Carlo methods of numerical simulation supplemented by the frames method. The numerical experiment was carried out using the program tool Mathcad Professional

Gene silencing in tick cell lines using small interfering or long double-stranded RNA

Gene silencing by RNA interference (RNAi) is an important research tool in many areas of biology. To effectively harness the power of this technique in order to explore tick functional genomics and tick-microorganism interactions, optimised parameters for RNAi-mediated gene silencing in tick cells need to be established. Ten cell lines from four economically important ixodid tick genera (Amblyomma, Hyalomma, Ixodes and Rhipicephalus including the sub-species Boophilus) were used to examine key parameters including small interfering RNA (siRNA), double stranded RNA (dsRNA), transfection reagent and incubation time for silencing virus reporter and endogenous tick genes. Transfection reagents were essential for the uptake of siRNA whereas long dsRNA alone was taken up by most tick cell lines. Significant virus reporter protein knockdown was achieved using either siRNA or dsRNA in all the cell lines tested. Optimum conditions varied according to the cell line. Consistency between replicates and duration of incubation with dsRNA were addressed for two Ixodes scapularis cell lines; IDE8 supported more consistent and effective silencing of the endogenous gene subolesin than ISE6, and highly significant knockdown of the endogenous gene 2I1F6 in IDE8 cells was achieved within 48 h incubation with dsRNA. In summary, this study shows that gene silencing by RNAi in tick cell lines is generally more efficient with dsRNA than with siRNA but results vary between cell lines and optimal parameters need to be determined for each experimental system