Dynamically variable step search motion estimation algorithm and a dynamically reconfigurable hardware for its implementation

Motion Estimation (ME) is the most computationally intensive part of video compression and video enhancement systems. For the recently available High Definition (HD) video formats, the computational complexity of De full search (FS) ME algorithm is prohibitively high, whereas the PSNR obtained by fast search ME algorithms is low. Therefore, ill this paper, we present Dynamically Variable Step Search (DVSS) ME algorithm for Processing high definition video formats and a dynamically reconfigurable hardware efficiently implementing DVSS algorithm. The architecture for efficiently implementing DVSS algorithm. The simulation results showed that DVSS algorithm performs very close to FS algorithm by searching much fewer search locations than FS algorithm and it outperforms successful past search ME algorithms by searching more search locations than these algorithms. The proposed hardware is implemented in VHDL and is capable, of processing high definition video formats in real time. Therefore, it can be used in consumer electronics products for video compression, frame rate up-conversion and de-interlacing(1)

PONDER - A Real time software backend for pulsar and IPS observations at the Ooty Radio Telescope

This paper describes a new real-time versatile backend, the Pulsar Ooty Radio Telescope New Digital Efficient Receiver (PONDER), which has been designed to operate along with the legacy analog system of the Ooty Radio Telescope (ORT). PONDER makes use of the current state of the art computing hardware, a Graphical Processing Unit (GPU) and sufficiently large disk storage to support high time resolution real-time data of pulsar observations, obtained by coherent dedispersion over a bandpass of 16 MHz. Four different modes for pulsar observations are implemented in PONDER to provide standard reduced data products, such as time-stamped integrated profiles and dedispersed time series, allowing faster avenues to scientific results for a variety of pulsar studies. Additionally, PONDER also supports general modes of interplanetary scintillation (IPS) measurements and very long baseline interferometry data recording. The IPS mode yields a single polarisation correlated time series of solar wind scintillation over a bandwidth of about four times larger (16 MHz) than that of the legacy system as well as its fluctuation spectrum with high temporal and frequency resolutions. The key point is that all the above modes operate in real time. This paper presents the design aspects of PONDER and outlines the design methodology for future similar backends. It also explains the principal operations of PONDER, illustrates its capabilities for a variety of pulsar and IPS observations and demonstrates its usefulness for a variety of astrophysical studies using the high sensitivity of the ORT.Comment: 25 pages, 14 figures, Accepted by Experimental Astronom

Market leadership through technology – Backward compatibility in the U.S. Handheld Video Game Industry

The introduction of a new product generation forces incumbents in network industries to rebuild their installed base to maintain an advantage over potential entrants. We study if backward compatibility moderates this process of rebuilding an installed base. Using a structural model of the U.S. market for handheld game consoles, we show that backward compatibility lets incumbents transfer network effects from the old generation to the new to some extent but that it also reduces supply of new software. We examine the tradeoff between technological progress and backward compatibility and find that backward compatibility matters less if there is a large technological leap between two generations. We subsequently use our results to assess the role of backward compatibility as a strategy to sustain market leadership

Real-time human action recognition on an embedded, reconfigurable video processing architecture

Copyright @ 2008 Springer-Verlag.In recent years, automatic human motion recognition has been widely researched within the computer vision and image processing communities. Here we propose a real-time embedded vision solution for human motion recognition implemented on a ubiquitous device. There are three main contributions in this paper. Firstly, we have developed a fast human motion recognition system with simple motion features and a linear Support Vector Machine (SVM) classifier. The method has been tested on a large, public human action dataset and achieved competitive performance for the temporal template (eg. “motion history image”) class of approaches. Secondly, we have developed a reconfigurable, FPGA based video processing architecture. One advantage of this architecture is that the system processing performance can be reconfiured for a particular application, with the addition of new or replicated processing cores. Finally, we have successfully implemented a human motion recognition system on this reconfigurable architecture. With a small number of human actions (hand gestures), this stand-alone system is performing reliably, with an 80% average recognition rate using limited training data. This type of system has applications in security systems, man-machine communications and intelligent environments.DTI and Broadcom Ltd

The Federal Information Security Management Act of 2002: A Potemkin Village

Due to the daunting possibilities of cyberwarfare, and the ease with which cyberattacks may be conducted, the United Nations has warned that the next world war could be initiated through worldwide cyberattacks between countries. In response to the growing threat of cyberwarfare and the increasing importance of information security, Congress passed the Federal Information Security Management Act of 2002 (FISMA). FISMA recognizes the importance of information security to the national economic and security interests of the United States. However, this Note argues that FISMA has failed to significantly bolster information security, primarily because FISMA treats information security as a technological problem and not an economic problem. This Note analyzes existing proposals to incentivize heightened software quality assurance, and proposes a new solution designed to strengthen federal information security in light of the failings of FISMA and the trappings of Congress’s 2001 amendment to the Computer Fraud and Abuse Act

A GPU based real-time software correlation system for the Murchison Widefield Array prototype

Modern graphics processing units (GPUs) are inexpensive commodity hardware that offer Tflop/s theoretical computing capacity. GPUs are well suited to many compute-intensive tasks including digital signal processing. We describe the implementation and performance of a GPU-based digital correlator for radio astronomy. The correlator is implemented using the NVIDIA CUDA development environment. We evaluate three design options on two generations of NVIDIA hardware. The different designs utilize the internal registers, shared memory and multiprocessors in different ways. We find that optimal performance is achieved with the design that minimizes global memory reads on recent generations of hardware. The GPU-based correlator outperforms a single-threaded CPU equivalent by a factor of 60 for a 32 antenna array, and runs on commodity PC hardware. The extra compute capability provided by the GPU maximises the correlation capability of a PC while retaining the fast development time associated with using standard hardware, networking and programming languages. In this way, a GPU-based correlation system represents a middle ground in design space between high performance, custom built hardware and pure CPU-based software correlation. The correlator was deployed at the Murchison Widefield Array 32 antenna prototype system where it ran in real-time for extended periods. We briefly describe the data capture, streaming and correlation system for the prototype array.Comment: 11 pages, to appear in PAS

FPGA implementation of real-time human motion recognition on a reconfigurable video processing architecture

In recent years, automatic human motion recognition has been widely researched within the computer vision and image processing communities. Here we propose a real-time embedded vision solution for human motion recognition implemented on a ubiquitous device. There are three main contributions in this paper. Firstly, we have developed a fast human motion recognition system with simple motion features and a linear Support Vector Machine(SVM) classifier. The method has been tested on a large, public human action dataset and achieved competitive performance for the temporal template (eg. ``motion history image") class of approaches. Secondly, we have developed a reconfigurable, FPGA based video processing architecture. One advantage of this architecture is that the system processing performance can be reconfigured for a particular application, with the addition of new or replicated processing cores. Finally, we have successfully implemented a human motion recognition system on this reconfigurable architecture. With a small number of human actions (hand gestures), this stand-alone system is performing reliably, with an 80% average recognition rate using limited training data. This type of system has applications in security systems, man-machine communications and intelligent environments