Variational optic flow on the Sony PlayStation 3 – accurate dense flow fields for real-time applications

While modern variational methods for optic flow computation offer dense flow fields and highly accurate results, their computational complexity has prevented their use in many real-time applications. With cheap modern parallel hardware such as the Sony PlayStation 3 new possibilities arise. For a linear and a nonlinear variant of the popular combined local-global (CLG) method, we present specific algorithms that are tailored towards real-time performance. They are based on bidirectional full multigrid methods with a full approximation scheme (FAS) in the nonlinear setting. Their parallelisation on the Cell hardware uses a temporal instead of a spatial decomposition, and processes operations in a vector-based manner. Memory latencies are reduced by a locality-preserving cache management and optimised access patterns. With images of size 316×252 pixels, we obtain dense flow fields for up to 210 frames per second

Low Cost Inertial Sensors for the Motion Track-ing and Orientation Estimation of Human Upper Limbs in Neurological Rehabilitation

This paper presents the feasibility of utilizing low cost inertial sensors such as those found in Sony Move, Nintendo Wii (Wii Remote with Wii MotionPlus) and smartphones for upper limb motion mon-itoring in neurorehabilitation. Kalman and complementary filters based on data fusion are used to estimate sensor 3D orientation. Furthermore, a two-segment kinematic model was developed to estimate limb segment position tracking. Performance has been compared with a high-accuracy measurement system using the Xsens MTx. The experimental results show that Sony Move, Wii and smartphones can be used for measuring upper limb orientation, while Sony Move and smartphones can also be used for specific applications of upper limb segment joint orientation and position tracking during neurorehabilitation. Sony Move’s accuracy is within 1.5° for Roll and Pitch and 2.5° for Yaw and position tracking to within 0.5 cm over a 10 cm movement. This accuracy in measurement is thought to be adequate for upper limb orientation and position tracking. Low cost inertial sensors can be used for the accurate assessment/measurement of upper limb movement of patients with neurological disorders and also makes it a low cost replacement for upper limb motion measurements. The low cost inertial sensing systems were shown to be able to accurately measure upper limb joint orienta-tion and position during neurorehabilitation

Implementation of Open Source applications “Serious Game” for rehabilitation

Serious Games and Virtual Reality (VR) are present nowadays as an alternative to traditional rehabilitation therapies. This project describes the workflow to develop videogames for health monitoring as well as a source of entertainment for physiotherapy patients, primarily patients that suffer hemiparesis caused by a neurological disease like a stroke. We propose the last version of Microsoft Kinect sensors as low cost game controller and the software Unity to develop Open Source Rehabilitation Serious Games. These Serious Games try to imitate physiotherapy sessions performed in movement recovery therapies, reducing the waiting list of patients together with time and costs to hospitals. The premise is that the gameplay makes patients execute upper body exercises alongside equilibrium training, meanwhile they are monitored extracting useful data and results for the physicians.Ingeniería Biomédic

The application of parallel processing techniques to computationally intensive biomedical imaging studies

The landscape of modern computing is changing. While Moore’s law is currently holding and the number of transistors that can be produced on a given area of a chip is still growing exponentially, the practice of improving performance by increasing the clock frequency of a single processor is reaching its limit. Instead, the focus has shifted to applying multiple processors to solving a single problem, a methodology known as parallel processing. Parallel processing has the potential to overcome many of the shortcomings of linear processing, but also presents a number of unique challenges. This dissertation explores the potential benefits of parallel processing by examining the application of a near-field coded aperture simulator on a parallel cluster and contrasting its implementation and performance with previously written simulators for serial processors. The platform used is a cluster of Sony PlayStation 3’s; featuring the IBM developed Cell Broadband Engine Architecture. It was found that the PS3’s were capable of producing performance gains of around forty times an equivalently priced conventional processor, with the capability of easily scaling the system by adding or removing nodes as required. However, this comes at the cost of a much increased burden on the developer. Apart from the core application, a great deal of code must be written to handle communication and synchronization between nodes, a task which can at times be very complex. In addition, a number of tools available for serial processors, such as highly efficient compilers, advanced development environments and many standardized libraries cannot be applied in a parallel environment. The main conclusions drawn from this research are that while the potential gains of parallel processing are enormous, allowing attainable solutions to problems that were previously too costly, the costs of development are prohibitive. Still, parallel processing is the natural next step in modern computing, and it is only a matter of time before its idiosyncrasies are solved

Playing at a Distance

An essential exploration of video game aesthetic that decenters the human player and challenges what it means to play. Do we play video games or do video games play us? Is nonhuman play a mere paradox or the future of gaming? And what do video games have to do with quantum theory? In Playing at a Distance, Sonia Fizek engages with these and many more daunting questions, forging new ways to think and talk about games and play that decenter the human player and explore a variety of play formats and practices that require surprisingly little human action. Idling in clicker games, wandering in walking simulators, automating gameplay with bots, or simply watching games rather than playing them—Fizek shows how these seemingly marginal cases are central to understanding how we play in the digital age. Introducing the concept of distance, Fizek reorients our view of computer-mediated play. To “play at a distance,” she says, is to delegate the immediate action to the machine and to become participants in an algorithmic spectacle. Distance as a media aesthetic framework enables the reader to come to terms with the ambiguity and aesthetic diversity of play. Drawing on concepts from philosophy, media theory, and posthumanism, as well as cultural and film studies, Playing at a Distance invites a wider understanding of what digital games and gaming are in all their diverse experiences and forms. In challenging the common perception of video games as inherently interactive, the book contributes to our understanding of the computer's influence on practices of play—and prods us to think more broadly about what it means to play

Accelerating Pattern Recognition Algorithms On Parallel Computing Architectures

The move to more parallel computing architectures places more responsibility on the programmer to achieve greater performance. The programmer must now have a greater understanding of the underlying architecture and the inherent algorithmic parallelism. Using parallel computing architectures for exploiting algorithmic parallelism can be a complex task. This dissertation demonstrates various techniques for using parallel computing architectures to exploit algorithmic parallelism. Specifically, three pattern recognition (PR) approaches are examined for acceleration across multiple parallel computing architectures, namely field programmable gate arrays (FPGAs) and general purpose graphical processing units (GPGPUs). Phase-only filter correlation for fingerprint identification was studied as the first PR approach. This approach\u27s sensitivity to angular rotations, scaling, and missing data was surveyed. Additionally, a novel FPGA implementation of this algorithm was created using fixed point computations, deep pipelining, and four computation phases. Communication and computation were overlapped to efficiently process large fingerprint galleries. The FPGA implementation showed approximately a 47 times speedup over a central processing unit (CPU) implementation with negligible impact on precision. For the second PR approach, a spiking neural network (SNN) algorithm for a character recognition application was examined. A novel FPGA implementation of the approach was developed incorporating a scalable modular SNN processing element (PE) to efficiently perform neural computations. The modular SNN PE incorporated streaming memory, fixed point computation, and deep pipelining. This design showed speedups of approximately 3.3 and 8.5 times over CPU implementations for 624 and 9,264 sized neural networks, respectively. Results indicate that the PE design could scale to process larger sized networks easily. Finally for the third PR approach, cellular simultaneous recurrent networks (CSRNs) were investigated for GPGPU acceleration. Particularly, the applications of maze traversal and face recognition were studied. Novel GPGPU implementations were developed employing varying quantities of task-level, data-level, and instruction-level parallelism to achieve efficient runtime performance. Furthermore, the performance of the face recognition application was examined across a heterogeneous cluster of multi-core and GPGPU architectures. A combination of multi-core processors and GPGPUs achieved roughly a 996 times speedup over a single-core CPU implementation. From examining these PR approaches for acceleration, this dissertation presents useful techniques and insight applicable to other algorithms to improve performance when designing a parallel implementation