10,388 research outputs found

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

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    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

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

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    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

    Self-Partial and Dynamic Reconfiguration Implementation for AES using FPGA

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    This paper addresses efficient hardware/software implementation approaches for the AES (Advanced Encryption Standard) algorithm and describes the design and performance testing algorithm for embedded system. Also, with the spread of reconfigurable hardware such as FPGAs (Field Programmable Gate Array) embedded cryptographic hardware became cost-effective. Nevertheless, it is worthy to note that nowadays, even hardwired cryptographic algorithms are not so safe. From another side, the self-reconfiguring platform is reported that enables an FPGA to dynamically reconfigure itself under the control of an embedded microprocessor. Hardware acceleration significantly increases the performance of embedded systems built on programmable logic. Allowing a FPGA-based MicroBlaze processor to self-select the coprocessors uses can help reduce area requirements and increase a system's versatility. The architecture proposed in this paper is an optimal hardware implementation algorithm and takes dynamic partially reconfigurable of FPGA. This implementation is good solution to preserve confidentiality and accessibility to the information in the numeric communication

    FPGA based remote code integrity verification of programs in distributed embedded systems

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    The explosive growth of networked embedded systems has made ubiquitous and pervasive computing a reality. However, there are still a number of new challenges to its widespread adoption that include scalability, availability, and, especially, security of software. Among the different challenges in software security, the problem of remote-code integrity verification is still waiting for efficient solutions. This paper proposes the use of reconfigurable computing to build a consistent architecture for generation of attestations (proofs) of code integrity for an executing program as well as to deliver them to the designated verification entity. Remote dynamic update of reconfigurable devices is also exploited to increase the complexity of mounting attacks in a real-word environment. The proposed solution perfectly fits embedded devices that are nowadays commonly equipped with reconfigurable hardware components that are exploited to solve different computational problems

    An Energy-Efficient Reconfigurable DTLS Cryptographic Engine for End-to-End Security in IoT Applications

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    This paper presents a reconfigurable cryptographic engine that implements the DTLS protocol to enable end-to-end security for IoT. This implementation of the DTLS engine demonstrates 10x reduction in code size and 438x improvement in energy-efficiency over software. Our ECC primitive is 237x and 9x more energy-efficient compared to software and state-of-the-art hardware respectively. Pairing the DTLS engine with an on-chip RISC-V allows us to demonstrate applications beyond DTLS with up to 2 orders of magnitude energy savings.Comment: Published in 2018 IEEE International Solid-State Circuits Conference (ISSCC

    An Energy-Efficient Reconfigurable DTLS Cryptographic Engine for End-to-End Security in IoT Applications

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    This paper presents a reconfigurable cryptographic engine that implements the DTLS protocol to enable end-to-end security for IoT. This implementation of the DTLS engine demonstrates 10x reduction in code size and 438x improvement in energy-efficiency over software. Our ECC primitive is 237x and 9x more energy-efficient compared to software and state-of-the-art hardware respectively. Pairing the DTLS engine with an on-chip RISC-V allows us to demonstrate applications beyond DTLS with up to 2 orders of magnitude energy savings.Comment: Published in 2018 IEEE International Solid-State Circuits Conference (ISSCC
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