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  • Open Access

    ARTICLE

    Review on Video Object Tracking Based on Deep Learning

    Fangming Bi1,2, Xin Ma1,2, Wei Chen1,2,*, Weidong Fang3, Huayi Chen1,2, Jingru Li1,2, Biruk Assefa1,4

    Journal of New Media, Vol.1, No.2, pp. 63-74, 2019, DOI:10.32604/jnm.2019.06253

    Abstract Video object tracking is an important research topic of computer vision, which finds a wide range of applications in video surveillance, robotics, human-computer interaction and so on. Although many moving object tracking algorithms have been proposed, there are still many difficulties in the actual tracking process, such as illumination change, occlusion, motion blurring, scale change, self-change and so on. Therefore, the development of object tracking technology is still challenging. The emergence of deep learning theory and method provides a new opportunity for the research of object tracking, and it is also the main theoretical framework for the research of moving… More >

  • Open Access

    ARTICLE

    A HEVC Video Steganalysis Algorithm Based on PU Partition Modes

    Zhonghao Li1, Laijin Meng1, Shutong Xu1, Zhaohong Li1,2,*, Yunqing Shi3, Yuanchang Liang1

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 563-574, 2019, DOI:10.32604/cmc.2019.05565

    Abstract Steganalysis is a technique used for detecting the existence of secret information embedded into cover media such as images and videos. Currently, with the higher speed of the Internet, videos have become a kind of main methods for transferring information. The latest video coding standard High Efficiency Video Coding (HEVC) shows better coding performance compared with the H.264/AVC standard published in the previous time. Therefore, since the HEVC was published, HEVC videos have been widely used as carriers of hidden information.
    In this paper, a steganalysis algorithm is proposed to detect the latest HEVC video steganography method which is based… More >

  • Open Access

    ARTICLE

    Secure Video Streaming with Lightweight Cipher PRESENT in an SDN Testbed

    Pengcheng Liu1, †, Xiaojun Wang1, †, S. R. Chaudhry1, Khalid Javeed2, Yue Ma3, *, Martin Collier1

    CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 353-363, 2018, DOI:10.32604/cmc.2018.04142

    Abstract The combination of traditional processors and Field Programmable Gate Arrays (FPGA) is shaping the future networking platform for intensive computation in resource-constrained networks and devices. These networks present two key challenges of security and resource limitations. Lightweight ciphers are suitable to provide data security in such constrained environments. Implementing the lightweight PRESENT encryption algorithm in a reconfigurable platform (FPGAs) can offer secure communication service and flexibility. This paper presents hardware acceleration of security primitives in SDN using NETFPGA-10G. We implement an efficient design of the PRESENT algorithm for faster, smaller and lower power consumption hardware circuit using Verilog. We evaluate… More >

  • Open Access

    ARTICLE

    Defining Embedding Distortion for Intra Prediction Mode-Based Video Steganography

    Qiankai Nie1, Xuba Xu1, Bingwen Feng1,*, Leo Yu Zhang2

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 59-70, 2018, DOI:10.3970/cmc.2018.055.059

    Abstract In this paper, an effective intra prediction mode-based video strganography is proposed. Secret messages are embedded during the intra prediction of the video encoding without causing large embedding impact. The influence on the sum of absolute difference (SAD) in intra prediction modes (IPMs) reversion phenomenon is sharp when modifying IPMs. It inspires us to take the SAD prediction deviation (SPD) to define the distortion function. What is more, the mapping rule between IPMs and the codewords is introduced to further reduce the SPD values of each intra block. Syndrome-trellis code (STC) is used as the practical embedding implementation. Experimental results… More >

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