Integración MPlayer-OpenSVC en el procesador multinúcleo OMAP3530

La constante evolución de dispositivos portátiles multimedia que se ha producido en la última década ha provocado que hoy en día se disponga de una amplia variedad de dispositivos con capacidad para reproducir contenidos multimedia. En consecuencia, la reproducción de esos contenidos en dichos terminales lleva asociada disponer de procesadores que soporten una alta carga computacional, ya que las tareas de descodificación y presentación de video así lo requieren. Sin embargo, un procesador potente trabajando a elevadas frecuencias provoca un elevado consumo de la batería, y dado que se pretende trabajar con dispositivos portátiles, la vida útil de la batería se convierte en un asunto de especial importancia. La problemática que se plantea se ha convertido en una de las principales líneas de investigación del Grupo de Investigación GDEM (Grupo de Diseño Electrónico y Microelectrónico). En esta línea de trabajo, se persigue cómo optimizar el consumo de energía en terminales portables desde el punto de vista de la reducción de la calidad de experiencia del usuario a cambio de una mayor autonomía del terminal. Por tanto, para lograr esa reducción de la calidad de experiencia mencionada, se requiere un estándar de codificación de vídeo que así lo permita. El Grupo de Investigación GDEM cuenta con experiencia en el estándar de vídeo escalable H.264/SVC, el cual permite degradar la calidad de experiencia en función de las necesidades/características del dispositivo. Más concretamente, un video escalable contiene embebidas distintas versiones del video original que pueden ser descodificadas en diferentes resoluciones, tasas de cuadro y calidades (escalabilidades espacial, temporal y de calidad respectivamente), permitiendo una adaptación rápida y muy flexible. Seleccionado el estándar H.264/SVC para las tareas de vídeo, se propone trabajar con Mplayer, un reproductor de vídeos de código abierto (open source), al cual se le ha integrado un descodificador para vídeo escalable denominado OpenSVC. Por último, como dispositivo portable se trabajará con la plataforma de desarrollo BeagleBoard, un sistema embebido basado en el procesador OMAP3530 que permite modificar la frecuencia de reloj y la tensión de alimentación dinámicamente reduciendo de este modo el consumo del terminal. Este procesador a su vez contiene integrados un procesador de propósito general (ARM Cortex-A8) y un procesador digital de señal (DSP TMS320C64+TM). Debido a la alta carga computacional de la descodificación de vídeos escalables y la escasa optimización del ARM para procesamiento de datos, se propone llevar a cabo la ejecución de Mplayer en el ARM y encargar la tarea de descodificación al DSP, con la finalidad de reducir el consumo y por tanto aumentar la vida útil del sistema embebido sobre el cual se ejecutará la aplicación desarrollada. Una vez realizada esa integración, se llevará a cabo una caracterización del descodificador alojado en el DSP a través de una serie de medidas de rendimiento y se compararán los resultados con los obtenidos en el proceso de descodificación realizado únicamente en el ARM. ABSTRACT During the last years, the multimedia portable terminals have gradually evolved causing that nowadays a several range of devices with the ability of playing multimedia contents are easily available for everyone. Consequently, those multimedia terminals must have high-performance processors to play those contents because the coding and decoding tasks demand high computational load. However, a powerful processor performing to high frequencies implies higher battery consumption, and this issue has become one of the most important problems in the development cycle of a portable terminal. The power/energy consumption optimization on multimedia terminals has become in one the most significant work lines in the Electronic and Microelectronic Research Group of the Universidad Politécnica de Madrid. In particular, the group is researching how to reduce the user‟s Quality of Experience (QoE) quality in exchange for increased battery life. In order to reduce the Quality of Experience (QoE), a standard video coding that allows this operation is required. The H.264/SVC allows reducing the QoE according to the needs/characteristics of the terminal. Specifically, a scalable video contains different versions of original video embedded in an only one video stream, and each one of them can be decoded in different resolutions, frame rates and qualities (spatial, temporal and quality scalabilities respectively). Once the standard video coding is selected, a multimedia player with support for scalable video is needed. Mplayer has been proposed as a multimedia player, whose characteristics (open-source, enormous flexibility and scalable video decoder called OpenSVC) are the most suitable for the aims of this Master Thesis. Lastly, the embedded system BeagleBoard, based on the multi-core processor OMAP3530, will be the development platform used in this project. The multimedia terminal architecture is based on a commercial chip having a General Purpose Processor (GPP – ARM Cortex A8) and a Digital Signal Processor (DSP, TMS320C64+™). Moreover, the processor OMAP3530 has the ability to modify the operating frequency and the supply voltage in a dynamic way in order to reduce the power consumption of the embedded system. So, the main goal of this Master Thesis is the integration of the multimedia player, MPlayer, executed at the GPP, and scalable video decoder, OpenSVC, executed at the DSP in order to distribute the computational load associated with the scalable video decoding task and to reduce the power consumption of the terminal. Once the integration is accomplished, the performance of the OpenSVC decoder executed at the DSP will be measured using different combinations of scalability values. The obtained results will be compared with the scalable video decoding performed at the GPP in order to show the low optimization of this kind of architecture for decoding tasks in contrast to DSP architecture.

Rapid prototyping framework for visual control of autonomous micro aerial vehicles

Rapid prototyping environments can speed up the research of visual control algorithms. We have designed and implemented a software framework for fast prototyping of visual control algorithms for Micro Aerial Vehicles (MAV). We have applied a combination of a proxy-based network communication architecture and a custom Application Programming Interface. This allows multiple experimental configurations, like drone swarms or distributed processing of a drone’s video stream. Currently, the framework supports a low-cost MAV: the Parrot AR.Drone. Real tests have been performed on this platform and the results show comparatively low figures of the extra communication delay introduced by the framework, while adding new functionalities and flexibility to the selected drone. This implementation is open-source and can be downloaded from www.vision4uav.com/?q=VC4MAV-FW

A vision-based strategy for autonomous aerial refueling tasks

Autonomous aerial refueling is a key enabling technology for both manned and unmanned aircraft where extended flight duration or range are required. The results presented within this paper offer one potential vision-based sensing solution, together with a unique test environment. A hierarchical visual tracking algorithm based on direct methods is proposed and developed for the purposes of tracking a drogue during the capture stage of autonomous aerial refueling, and of estimating its 3D position. Intended to be applied in real time to a video stream from a single monocular camera mounted on the receiver aircraft, the algorithm is shown to be highly robust, and capable of tracking large, rapid drogue motions within the frame of reference. The proposed strategy has been tested using a complex robotic testbed and with actual flight hardware consisting of a full size probe and drogue. Results show that the vision tracking algorithm can detect and track the drogue at real-time frame rates of more than thirty frames per second, obtaining a robust position estimation even with strong motions and multiple occlusions of the drogue.

Motion vector encryption in multimedia streaming

Streaming video application requires high security as well as high computational performance. In video encryption, traditional selective algorithms have been used to partially encrypt the relatively important data in order to satisfy the streaming performance requirement. Most video selective encryption algorithms are inherited from still image encryption algorithms, the encryption on motion vector data is not considered. The assumption is that motion vector data are not as important as pixel image data. Unfortunately, in some cases, motion vector itself may be sufficient enough to leak out useful video information. Normally motion vector data consume over half of the whole video stream bandwidth, neglecting their security may be unwise. In this paper, we target this security problem and illustrate attacks at two different levels that can restore useful video information using motion vectors only. Further, an information analysis is made and a motion vector information model is built. Based on this model, we describe a new motion vector encryption algorithm called MVEA. We show the experimental results of MVEA. The security strength and performance of the algorithm are also evaluated.

A scalable multimedia content processing framework with application to TV shopping

The advent of smart TVs has reshaped the TV-consumer interaction by combining TVs with mobile-like applications and access to the Internet. However, consumers are still unable to seamlessly interact with the contents being streamed. An example of such limitation is TV shopping, in which a consumer makes a purchase of a product or item displayed in the current TV show. Currently, consumers can only stop the current show and attempt to find a similar item in the Web or an actual store. It would be more convenient if the consumer could interact with the TV to purchase interesting items. ^ Towards the realization of TV shopping, this dissertation proposes a scalable multimedia content processing framework. Two main challenges in TV shopping are addressed: the efficient detection of products in the content stream, and the retrieval of similar products given a consumer-selected product. The proposed framework consists of three components. The first component performs computational and temporal aware multimedia abstraction to select a reduced number of frames that summarize the important information in the video stream. By both reducing the number of frames and taking into account the computational cost of the subsequent detection phase, this component component allows the efficient detection of products in the stream. The second component realizes the detection phase. It executes scalable product detection using multi-cue optimization. Additional information cues are formulated into an optimization problem that allows the detection of complex products, i.e., those that do not have a rigid form and can appear in various poses. After the second component identifies products in the video stream, the consumer can select an interesting one for which similar ones must be located in a product database. To this end, the third component of the framework consists of an efficient, multi-dimensional, tree-based indexing method for multimedia databases. The proposed index mechanism serves as the backbone of the search. Moreover, it is able to efficiently bridge the semantic gap and perception subjectivity issues during the retrieval process to provide more relevant results.^

ENCARA: real-time detection of frontal faces

[EN]This paper describes a real-time approach for face detection and selection of frontal views, for further processing. Typically, face detection papers provide results for a set of single images but the problem of face detection in video streams rarely is tackled. Instead of performing an exhaustive search for every video stream frame a set of opportunistic ideas applied in a cascade fashion and based on temporal and spatial coherence provide promising results in real-time.

Run-time Scalable Architecture for Deblocking Filtering in H.264/AVC-SVC Video Codecs

Systems relying on fixed hardware components with a static level of parallelism can suffer from an underuse of logical resources, since they have to be designed for the worst-case scenario. This problem is especially important in video applications due to the emergence of new flexible standards, like Scalable Video Coding (SVC), which offer several levels of scalability. In this paper, Dynamic and Partial Reconfiguration (DPR) of modern FPGAs is used to achieve run-time variable parallelism, by using scalable architectures where the size can be adapted at run-time. Based on this proposal, a scalable Deblocking Filter core (DF), compliant with the H.264/AVC and SVC standards has been designed. This scalable DF allows run-time addition or removal of computational units working in parallel. Scalability is offered together with a scalable parallelization strategy at the macroblock (MB) level, such that when the size of the architecture changes, MB filtering order is modified accordingly

Improved matching criterion for frame rate upconversion with trilateral filtering

Frame rate upconversion (FRUC) is an important post-processing technique to enhance the visual quality of low frame rate video. A major, recent advance in this area is FRUC based on trilateral filtering which novelty mainly derives from the combination of an edge-based motion estimation block matching criterion with the trilateral filter. However, there is still room for improvement, notably towards reducing the size of the uncovered regions in the initial estimated frame, this means the estimated frame before trilateral filtering. In this context, proposed is an improved motion estimation block matching criterion where a combined luminance and edge error metric is weighted according to the motion vector components, notably to regularise the motion field. Experimental results confirm that significant improvements are achieved for the final interpolated frames, reaching PSNR gains up to 2.73 dB, on average, regarding recent alternative solutions, for video content with varied motion characteristics.

Personalised placement in networked video

Personalised video can be achieved by inserting objects into a video play-out according to the viewer's profile. Content which has been authored and produced for general broadcast can take on additional commercial service features when personalised either for individual viewers or for groups of viewers participating in entertainment, training, gaming or informational activities. Although several scenarios and use-cases can be envisaged, we are focussed on the application of personalised product placement. Targeted advertising and product placement are currently garnering intense interest in the commercial networked media industries. Personalisation of product placement is a relevant and timely service for next generation online marketing and advertising and for many other revenue generating interactive services. This paper discusses the acquisition and insertion of media objects into a TV video play-out stream where the objects are determined by the profile of the viewer. The technology is based on MPEG-4 standards using object based video and MPEG-7 for metadata. No proprietary technology or protocol is proposed. To trade the objects into the video play-out, a Software-as-a-Service brokerage platform based on intelligent agent technology is adopted. Agencies, libraries and service providers are represented in a commercial negotiation to facilitate the contractual selection and usage of objects to be inserted into the video play-out.

TV Recommendation and Personalization Systems: Integrating Broadcast and Video On-demand Services

he expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.

Automatic front-crawl temporal phase detection using adaptive filtering of inertial signals

This study introduces a novel approach for automatic temporal phase detection and inter-arm coordination estimation in front-crawl swimming using inertial measurement units (IMUs). We examined the validity of our method by comparison against a video-based system. Three waterproofed IMUs (composed of 3D accelerometer, 3D gyroscope) were placed on both forearms and the sacrum of the swimmer. We used two underwater video cameras in side and frontal views as our reference system. Two independent operators performed the video analysis. To test our methodology, seven well-trained swimmers performed three 300 m trials in a 50 m indoor pool. Each trial was in a different coordination mode quantified by the index of coordination. We detected different phases of the arm stroke by employing orientation estimation techniques and a new adaptive change detection algorithm on inertial signals. The difference of 0.2 +/- 3.9% between our estimation and video-based system in assessment of the index of coordination was comparable to experienced operators' difference (1.1 +/- 3.6%). The 95% limits of agreement of the difference between the two systems in estimation of the temporal phases were always less than 7.9% of the cycle duration. The inertial system offers an automatic easy-to-use system with timely feedback for the study of swimming.

Transfer of MPEG-2 Transport Stream over MPLS

This study examines how MPEG-2 Transport Stream, used in DVB-T video transmission, can be reliably and efficiently transferred to remote locations over an MPLS network. All the relevant technologies used in this scenario are also discussed in the study. This study was done for Digita Oy, which is a major radio and television content distributor in Finland. The theoretical part of the study begins with the introduction to MPLS technology and continues with explanation of IP Multicast and its components. The fourth section discusses MPEG-2 and the formation and content of MPEG-2 Transport Stream. These technologies were studied in relevant literature and RFC documentation. After the theoretical part of the study, the test setup and the test cases are presented. The results of the test cases, and the conclusions that can be drawn based on them, are discussed in the last section of the study. The tests showed that it is possible to transfer digital video quite reliably over an MPLS network using IP Multicast. By configuring the equipment correctly, the recovery time of the network in case of a failure can be shortened remarkably. Also, the unwanted effect of other traffic on the critical video traffic can be eliminated by defining the Quality of Service parameters correctly. There are, however, some issues that need to be tested further before this setup can be used in broadcast networks. Reliable operation of IP Multicast and proper error correction are the main subjects for future testing.

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

Visual SLAM for underwater vehicles using video velocity log and natural landmarks

A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system

Automatic recognition of fish from video sequences

The problem of automatic recognition of the fish from the video sequences is discussed in this Master’s Thesis. This is a very urgent issue for many organizations engaged in fish farming in Finland and Russia because the process of automation control and counting of individual species is turning point in the industry. The difficulties and the specific features of the problem have been identified in order to find a solution and propose some recommendations for the components of the automated fish recognition system. Methods such as background subtraction, Kalman filtering and Viola-Jones method were implemented during this work for detection, tracking and estimation of fish parameters. Both the results of the experiments and the choice of the appropriate methods strongly depend on the quality and the type of a video which is used as an input data. Practical experiments have demonstrated that not all methods can produce good results for real data, whereas on synthetic data they operate satisfactorily.