Bounded non-deterministic planning for multimedia adaptation

This paper proposes a novel combination of artificial intelligence planning and other techniques for improving decision-making in the context of multi-step multimedia content adaptation. In particular, it describes a method that allows decision-making (selecting the adaptation to perform) in situations where third-party pluggable multimedia conversion modules are involved and the multimedia adaptation planner does not know their exact adaptation capabilities. In this approach, the multimedia adaptation planner module is only responsible for a part of the required decisions; the pluggable modules make additional decisions based on different criteria. We demonstrate that partial decision-making is not only attainable, but also introduces advantages with respect to a system in which these conversion modules are not capable of providing additional decisions. This means that transferring decisions from the multi-step multimedia adaptation planner to the pluggable conversion modules increases the flexibility of the adaptation. Moreover, by allowing conversion modules to be only partially described, the range of problems that these modules can address increases, while significantly decreasing both the description length of the adaptation capabilities and the planning decision time. Finally, we specify the conditions under which knowing the partial adaptation capabilities of a set of conversion modules will be enough to compute a proper adaptation plan.

Adaptable Bayesian classifier for spatiotemporal nonparametric moving object detection strategies

Electronic devices endowed with camera platforms require new and powerful machine vision applications, which commonly include moving object detection strategies. To obtain high-quality results, the most recent strategies estimate nonparametrically background and foreground models and combine them by means of a Bayesian classifier. However, typical classifiers are limited by the use of constant prior values and they do not allow the inclusion of additional spatiodependent prior information. In this Letter, we propose an alternative Bayesian classifier that, unlike those reported before, allows the use of additional prior information obtained from any source and depending on the spatial position of each pixel.

A framework for the analysis and optimization of encoding latency for multiview video

We present a novel framework for the analysis and optimization of encoding latency for multiview video. Firstly, we characterize the elements that have an influence in the encoding latency performance: (i) the multiview prediction structure and (ii) the hardware encoder model. Then, we provide algorithms to find the encoding latency of any arbitrary multiview prediction structure. The proposed framework relies on the directed acyclic graph encoder latency (DAGEL) model, which provides an abstraction of the processing capacity of the encoder by considering an unbounded number of processors. Using graph theoretic algorithms, the DAGEL model allows us to compute the encoding latency of a given prediction structure, and determine the contribution of the prediction dependencies to it. As an example of DAGEL application, we propose an algorithm to reduce the encoding latency of a given multiview prediction structure up to a target value. In our approach, a minimum number of frame dependencies are pruned, until the latency target value is achieved, thus minimizing the degradation of the rate-distortion performance due to the removal of the prediction dependencies. Finally, we analyze the latency performance of the DAGEL derived prediction structures in multiview encoders with limited processing capacity.

Refined facial disparity maps for automatic creation of 3D avatars

We propose a new method to automatically refine a facial disparity map obtained with standard cameras and under conventional illumination conditions by using a smart combination of traditional computer vision and 3D graphics techniques. Our system inputs two stereo images acquired with standard (calibrated) cameras and uses dense disparity estimation strategies to obtain a coarse initial disparity map, and SIFT to detect and match several feature points in the subjects face. We then use these points as anchors to modify the disparity in the facial area by building a Delaunay triangulation of their convex hull and interpolating their disparity values inside each triangle. We thus obtain a refined disparity map providing a much more accurate representation of the the subjects facial features. This refined facial disparity map may be easily transformed, through the camera calibration parameters, into a depth map to be used, also automatically, to improve the facial mesh of a 3D avatar to match the subjects real human features.

Experimental investigation of radio signal propagation in scientific facilities for telerobotic applications

Understanding the radio signal transmission characteristics in the environment where the telerobotic application is sought is a key part of achieving a reliable wireless communication link between a telerobot and a control station. In this paper, wireless communication requirements and a case study of a typical telerobotic application in an underground facility at CERN are presented. Then, the theoretical and experimental characteristics of radio propagation are investigated with respect to time, distance, location and surrounding objects. Based on analysis of the experimental findings, we show how a commercial wireless system, such as Wi-Fi, can be made suitable for a case study application at CERN.

Energy Management Module for Mobile Robots in Hostile Environments

In hostile environments at CERN and other similar scientific facilities, having a reliable mobile robot system is essential for successful execution of robotic missions and to avoid situations of manual recovery of the robots in the event that the robot runs out of energy. Because of environmental constraints, such mobile robots are usually battery-powered and hence energy management and optimization is one of the key challenges in this field. The ability to know beforehand the energy consumed by various elements of the robot (such as locomotion, sensors, controllers, computers and communication) will allow flexibility in planning or managing the tasks to be performed by the robot.

Model Based On-Line Energy Prediction System for Semi-Autonomous Mobile Robots

Maximizing energy autonomy is a consistent challenge when deploying mobile robots in ionizing radiation or other hazardous environments. Having a reliable robot system is essential for successful execution of missions and to avoid manual recovery of the robots in environments that are harmful to human beings. For deployment of robots missions at short notice, the ability to know beforehand the energy required for performing the task is essential. This paper presents a on-line method for predicting energy requirements based on the pre-determined power models for a mobile robot. A small mobile robot, Khepera III is used for the experimental study and the results are promising with high prediction accuracy. The applications of the energy prediction models in energy optimization and simulations are also discussed along with examples of significant energy savings.

Haptic teleoperation of mobile robots for augmentation of operator perception in environments with low-wireless signal

Wireless teleoperation of field robots for maintenance, inspection and rescue missions is often performed in environments with low wireless connectivity, caused by signal losses from the environment and distance from the wireless transmitters. Various studies from the literature have addressed these problems with time-delay robust control systems and multi-hop wireless relay networks. However, such approaches do not solve the issue of how to present wireless data to the operator to avoid losing control of the robot. Despite the fact that teleoperation for maintenance often already involves haptic devices, no studies look at the possibility of using this existing feedback to aid operators in navigating within areas of variable wireless connectivity. We propose a method to incorporate haptic information into the velocity control of an omnidirectional robot to augment the operators perception of wireless signal strength in the remote environment. In this paper we introduce a mapping between wireless signal strength from multiple receivers to the force feedback of a 6 Degree of Freedom haptic master and evaluate the proposed approach using experimental data and randomly generated wireless maps

Spatial sampling methods for improved communication for wireless relay robots

Having reliable wireless communication in a network of mobile robots is an ongoing challenge, especially when the mobile robots are given tasks in hostile or harmful environments such as radiation environments in scientific facilities, tunnels with large metallic components and complicated geometries as found at CERN. In this paper, we propose a decentralised method for improving the wireless network throughput by optimizing the wireless relay robot position to receive the best wireless signal strength using implicit spatial diversity concepts and gradient-search algorithms. We experimentally demonstrate the effectiveness of the proposed solutions with a KUKA Youbot omni-directional mobile robot. The performance of the algorithms is compared under various scenarios in an underground scientific facility at CERN.

Efecto del tamaño de la ventana de promediado y la histéresis variable en algoritmos de handover horizontal en redes convergentes

En las redes convergentes inalámbricas, el traspaso horizontal entre distintos puntos de acceso de la red WLAN es una gran fuente de degradación de la calidad de la VoIP y otros servicios conversacionales en tiempo real. Esto es debido a que este tipo de redes no fueron concebidas originalmente para soportar este tipo de servicios, y los traspasos siguen un protocolo ¿cortar antes de realizar¿, produciéndose interrupciones en la comunicación motivadas por el tiempo que necesitan los terminales en volver a asociarse a la red. En este artículo se estudia el efecto que tienen el tamaño de la ventana de promediado de la señal, la histéresis variable y el retardo del handover por parecido entre potencia de puntos de acceso de destino sobre el número de traspasos y las caídas de la potencia de señal por debajo del valor de sensibilidad del terminal, causantes principales de las interrupciones en la comunicación, y, con ello, de la degradación de la calidad de las comunicaciones.

Despliegues de femtoceldas LTE en interiores comparación con otras tecnologías inalámbricas

Long Term Evolution (LTE) has appeared with the aim of improving the performance of 3G networks, increasing spectral efficiency and peak rates both at downlink and uplink, reducing latency and increasing flexibility of frequency allocation. Therefore, LTE is expected to have a key role in the development of wireless networks and services in the next years, and, of course, in specific dedicated in-building solutions. Due to that fact, an analysis of LTE performance in indoor scenarios in terms of capacity and grade of service is essential, as well as its comparison with other indoor solutions, pointing out the technical challenges derived, and describing and proposing performance assessment rules to be used in LTE deployments.

Biomechanical evaluation of the singing voice

Teaching the adequate use of the singing voice conveys a lot of knowledge in musical performance as well as in objective estimation techniques involving the use of air, muscles, room and body acoustics, and the tuning of a fine instrument as the human voice. Although subjective evaluation and training is a very delicate task to be carried out only by expert singers, biomedical engineering may help contributing with well-funded methodologies developed for the study of voice pathology. The present work is a preliminary study of exploratory character describing the performance of a student singer in a regular classroom under the point of view of vocal fold biomechanics. Estimates of biomechanical parameters obtained from singing voice are given and their potential use is discussed.

Estimating tremor in Vocal Fold Biomechanics for Neurological Disease characterisation

Neurological Diseases (ND) are affecting larger segments of aging population every year. Treatment is dependent on expensive accurate and frequent monitoring. It is well known that ND leave correlates in speech and phonation. The present work shows a method to detect alterations in vocal fold tension during phonation. These may appear either as hypertension or as cyclical tremor. Estimations of tremor may be produced by auto-regressive modeling of the vocal fold tension series in sustained phonation. The correlates obtained are a set of cyclicality coefficients, the frequency and the root mean square amplitude of the tremor. Statistical distributions of these correlates obtained from a set of male and female subjects are presented. Results from five study cases of female voice are also given.

Classical vs. biometric features in the 2013 speaker recognition evaluation in mobile environments

MFCC coefficients extracted from the power spectral density of speech as a whole, seems to have become the de facto standard in the area of speaker recognition, as demonstrated by its use in almost all systems submitted to the 2013 Speaker Recognition Evaluation (SRE) in Mobile Environment [1], thus relegating to background this component of the recognition systems. However, in this article we will show that selecting the adequate speaker characterization system is as important as the selection of the classifier. To accomplish this we will compare the recognition rates achieved by different recognition systems that relies on the same classifier (GMM-UBM) but connected with different feature extraction systems (based on both classical and biometric parameters). As a result we will show that a gender dependent biometric parameterization with a simple recognition system based on GMM- UBM paradigm provides very competitive or even better recognition rates when compared to more complex classification systems based on classical features

Monitoring treatment of vocal fold paralysis by biomechanical analysis of voice

A case study of vocal fold paralysis treatment is described with the help of the voice quality analysis application BioMet®Phon. The case corresponds to a description of a 40 - year old female patient who was diagnosed of vocal fold paralysis following a cardio - pulmonar intervention which required intubation for 8 days and posterior tracheotomy for 15 days. The patient presented breathy and asthenic phon ation, and dysphagia. Six main examinations were conducted during a full year period that the treatment lasted consisting in periodic reviews including video - endostroboscopy, voice analysis and breathing function monitoring. The phoniatrician treatment inc luded 20 sessions of vocal rehabilitation, followed by an intracordal infiltration with Radiesse 8 months after the rehabilitation treatment started followed by 6 sessions of rehabilitation more. The videondoscopy and the voicing quality analysis refer a s ubstantial improvement in the vocal function with recovery in all the measures estimated (jitter, shimmer, mucosal wave contents, glottal closure, harmonic contents and biomechanical function analysis). The paper refers the procedure followed and the results obtained by comparing the longitudinal progression of the treatment, illustrating the utility of voice quality analysis tools in speech therapy.