The Experts below are selected from a list of 1740 Experts worldwide ranked by ideXlab platform

Tadashi Shibata - One of the best experts on this subject based on the ideXlab platform.

  • A multiple-candidate-regeneration-based Object Tracking System with enhanced learning capability by nearest neighbor classifier
    2013 IEEE International Symposium on Circuits and Systems (ISCAS), 2013
    Co-Authors: Pushe Zhao, Tadashi Shibata
    Abstract:

    We present a real-time Object Tracking System that employs the nearest neighbor classifier and the multiple candidate regeneration as the appearance model and the searching strategy. Based on the analysis of the likelihood measurement, a novel appearance model has been proposed, with an online learning strategy specifically designed for Tracking task. The number of templates is reduced to a small number and reliable template selection is realized. Because of its simplicity, the System can be efficiently built on hardware. The evaluation of the proposed System on challenging video sequences shows robust Tracking capability with accurate Tracking results. Hardware implementation of this System is also discussed and a processing speed much faster than the frame rate can be expected.

  • ISCAS - A multiple-candidate-regeneration-based Object Tracking System with enhanced learning capability by nearest neighbor classifier
    2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013
    Co-Authors: Pushe Zhao, Tadashi Shibata
    Abstract:

    We present a real-time Object Tracking System that employs the nearest neighbor classifier and the multiple candidate regeneration as the appearance model and the searching strategy. Based on the analysis of the likelihood measurement, a novel appearance model has been proposed, with an online learning strategy specifically designed for Tracking task. The number of templates is reduced to a small number and reliable template selection is realized. Because of its simplicity, the System can be efficiently built on hardware. The evaluation of the proposed System on challenging video sequences shows robust Tracking capability with accurate Tracking results. Hardware implementation of this System is also discussed and a processing speed much faster than the frame rate can be expected.

  • A Directional-Edge-Based Real-Time Object Tracking System Employing Multiple Candidate-Location Generation
    IEEE Transactions on Circuits and Systems for Video Technology, 2013
    Co-Authors: Pushe Zhao, He Li, Tadashi Shibata
    Abstract:

    We present a directional-edge-based Object Tracking System based on a field-programmable gate array (FPGA) that can process 640 × 480 resolution video sequences and provide the location of a predefined Object in real time. Inspired by biological principle, directional edge information is used to represent the Object features. Multiple candidate regeneration, a statistical method, has been developed to realize the Tracking function, and online learning is adopted to enhance the Tracking performance. Thanks to the hardware-implementation friendliness of the algorithm, an Object Tracking System has been very efficiently built on an FPGA, in order to realize a real-time Tracking capability. At the working frequency of 60 MHz, the main processing circuit can complete the processing of one frame of an image (640 × 480 pixels) in 0.1 ms in high-speed mode and 0.8 ms in high-accuracy mode. The experimental results demonstrate that this System can deal with various complex situations, including scene illumination changes, Object deformation, and partial occlusion. Based on the System built on the FPGA, we discuss the issue of very large-scale integrated chip implementation of the algorithm and self initialization of the System, i.e., the autonomous localization of the Tracking Object in the initial frame. Some potential solutions to the problems of multiple Object Tracking and full occlusion are also presented.

Pushe Zhao - One of the best experts on this subject based on the ideXlab platform.

  • A multiple-candidate-regeneration-based Object Tracking System with enhanced learning capability by nearest neighbor classifier
    2013 IEEE International Symposium on Circuits and Systems (ISCAS), 2013
    Co-Authors: Pushe Zhao, Tadashi Shibata
    Abstract:

    We present a real-time Object Tracking System that employs the nearest neighbor classifier and the multiple candidate regeneration as the appearance model and the searching strategy. Based on the analysis of the likelihood measurement, a novel appearance model has been proposed, with an online learning strategy specifically designed for Tracking task. The number of templates is reduced to a small number and reliable template selection is realized. Because of its simplicity, the System can be efficiently built on hardware. The evaluation of the proposed System on challenging video sequences shows robust Tracking capability with accurate Tracking results. Hardware implementation of this System is also discussed and a processing speed much faster than the frame rate can be expected.

  • ISCAS - A multiple-candidate-regeneration-based Object Tracking System with enhanced learning capability by nearest neighbor classifier
    2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013
    Co-Authors: Pushe Zhao, Tadashi Shibata
    Abstract:

    We present a real-time Object Tracking System that employs the nearest neighbor classifier and the multiple candidate regeneration as the appearance model and the searching strategy. Based on the analysis of the likelihood measurement, a novel appearance model has been proposed, with an online learning strategy specifically designed for Tracking task. The number of templates is reduced to a small number and reliable template selection is realized. Because of its simplicity, the System can be efficiently built on hardware. The evaluation of the proposed System on challenging video sequences shows robust Tracking capability with accurate Tracking results. Hardware implementation of this System is also discussed and a processing speed much faster than the frame rate can be expected.

  • A Directional-Edge-Based Real-Time Object Tracking System Employing Multiple Candidate-Location Generation
    IEEE Transactions on Circuits and Systems for Video Technology, 2013
    Co-Authors: Pushe Zhao, He Li, Tadashi Shibata
    Abstract:

    We present a directional-edge-based Object Tracking System based on a field-programmable gate array (FPGA) that can process 640 × 480 resolution video sequences and provide the location of a predefined Object in real time. Inspired by biological principle, directional edge information is used to represent the Object features. Multiple candidate regeneration, a statistical method, has been developed to realize the Tracking function, and online learning is adopted to enhance the Tracking performance. Thanks to the hardware-implementation friendliness of the algorithm, an Object Tracking System has been very efficiently built on an FPGA, in order to realize a real-time Tracking capability. At the working frequency of 60 MHz, the main processing circuit can complete the processing of one frame of an image (640 × 480 pixels) in 0.1 ms in high-speed mode and 0.8 ms in high-accuracy mode. The experimental results demonstrate that this System can deal with various complex situations, including scene illumination changes, Object deformation, and partial occlusion. Based on the System built on the FPGA, we discuss the issue of very large-scale integrated chip implementation of the algorithm and self initialization of the System, i.e., the autonomous localization of the Tracking Object in the initial frame. Some potential solutions to the problems of multiple Object Tracking and full occlusion are also presented.

Jung-hwan Ko - One of the best experts on this subject based on the ideXlab platform.

  • VCIP - Adaptive stereo Object Tracking System based-on block-based SSD algorithm and camera configuration parameter
    Visual Communications and Image Processing 2003, 2003
    Co-Authors: Jung-hwan Ko, Chang-ju Park
    Abstract:

    In this paper, an adaptive stereo Object Tracking System based on a block-based SSD(sum of squared difference) algorithm and camera configuration parameters is proposed. That is, by applying SSD algorithm to the reference image of the previous frame and the input image of the current frame, each location coordinate of a moving target in the right and left images are extracted and the respective shifted distances from the reference target position which is assumed to be at the origin in the initial frame are detected. Using the pan/tilt's moving angle calculated from the target's shifted distance and the configuration parameters of a stereo camera System, the block-mask size of a target Object can be adaptively determined. The target image segmented with this block mask is used as a reference image in the next stage of Tracking, and it is automatically updated according to the same procedure during the course of target Tracking. From some experiments using sequential 48 frames of the dynamic stereo image, it is analyzed that the horizontal and vertical stereo disparities on the target Object after stereo Tracking are kept to be very low values of 1.5 and 0.4 pixels on average, respectively.

  • Stereo Object Tracking System using variable window mask and optical BPEJTC
    Machine Vision and Three-Dimensional Imaging Systems for Inspection and Metrology II, 2002
    Co-Authors: Jung-hwan Ko
    Abstract:

    In this paper, a new stereo Object-Tracking System is proposed in which the variable window mask and the optical binary phase extraction joint transform correlator (BPEJTC) are used. Firstly, using the distance information from the stereo camera to the Tracking Object, the area of the Tracking Object is digitally extracted through a variable window mask. And, at the second step, by carrying out an optical BPEJTC between the reference image obtained from a variable window mask and the stereo input image, the coordinates of the Tracking Object's location are acquired, and then with these values, the convergence angle and the pan/tilt of the stereo Tracking camera can be finally controlled. Some experiments show that the proposed System is able to effectively extract the area of the target Object from the input image having the background noises and easily control the convergence angle and the pan/tilt of the stereo cameras with the obtained location values of a Tracking Object. From these experimental results, a feasibility of real-time implementation of the adaptive stereo Object Tracking System using the proposed algorithm is also suggested.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

  • Visual Information Processing - Real-time stereo Object Tracking System using the block-based window mask and optical BPEJTC
    Visual Information Processing X, 2001
    Co-Authors: Jung-hwan Ko
    Abstract:

    In this paper, we proposed a stereo Object Tracking System that can control the convergence angle and pan/tilt of cameras by using optical binary phase extraction joint transform correlator (BPEJTC) and can extract the Tracking Object from a complex background and foreground noises by using the block matching-based window mask. It is used to perceive and extract the Tracking Object from the foreground and complex background by using window mask of the block matching-based SAD(sum of absolute difference), and by using the optical BPEJTC of the phase type, which has improved the correlating properties of the conventional optical JTC(joint transform correlator) with the adaptive Object Tracking ability, the position values of moving target on the left and right images can be calculated. And, we can be controlling the convergence angle and pan/tilt of cameras by using this values. Therefore, real time stereo Object Tracking System, which could adapt to the changes in surrounding, can be implemented. From the experimental results, the proposed stereo Tracking System is found to track the Object adaptively under the complex circumstances and changing background noises and the possibility of real-time implementation of the proposed System by using the optical System is also suggested.

  • Real-time stereo Object Tracking System by using block matching algorithm and optical binary phase extraction joint transform correlator
    Optics Communications, 2001
    Co-Authors: Jung-hwan Ko
    Abstract:

    In this paper, we proposed a new adaptive stereo Object Tracking System that can control the convergence angle and pan/tilt of cameras by using optical binary phase extraction joint transform correlator and can extract the Tracking Object from a complex background and foreground noises by using the block-based mean square error algorithm. From the experimental results, the proposed stereo Tracking System is found to track the Object adaptively under the complex circumstances and changing background noises and the possibility of real-time implementation of the proposed System by using the optical System is also suggested.

Yan Zhang - One of the best experts on this subject based on the ideXlab platform.

  • ASICON - A novel low-cost FPGA-based real-time Object Tracking System
    2017 IEEE 12th International Conference on ASIC (ASICON), 2017
    Co-Authors: Ruyue Yuan, Linsheng Zhang, Yan Zhang
    Abstract:

    In current visual Object Tracking System, the CPU or GPU-based visual Object Tracking Systems have high computational cost and consume a prohibitive amount of power. Therefore, in this paper, to reduce computational burden of Camshift algorithm, we propose a novel visual Object Tracking algorithm by exploiting the properties of binary classifier and Kalman predictor. Moreover, we present a low-cost FPGA-based real-time Object Tracking hardware architecture. Extensive evaluations on OTB benchmark demonstrate that the proposed System has extremely compelling real-time, stability and robustness. The evaluation results show that the accuracy of our algorithm is about 53%, the overlap rate is about 50%, and the average speed is about 309 fps.

  • A novel low-cost FPGA-based real-time Object Tracking System
    2017 IEEE 12th International Conference on ASIC (ASICON), 2017
    Co-Authors: Ruyue Yuan, Linsheng Zhang, Yan Zhang
    Abstract:

    In current visual Object Tracking System, the CPU or GPU-based visual Object Tracking Systems have high computational cost and consume a prohibitive amount of power. Therefore, in this paper, to reduce computational burden of Camshift algorithm, we propose a novel visual Object Tracking algorithm by exploiting the properties of binary classifier and Kalman predictor. Moreover, we present a low-cost FPGA-based real-time Object Tracking hardware architecture. Extensive evaluations on OTB benchmark demonstrate that the proposed System has extremely compelling real-time, stability and robustness. The evaluation results show that the accuracy of our algorithm is about 53%, the overlap rate is about 50%, and the average speed is about 309 fps.

Khalid Munawar - One of the best experts on this subject based on the ideXlab platform.

  • FPGA/soft-processor based real-time Object Tracking System
    2009 5th Southern Conference on Programmable Logic (SPL), 2009
    Co-Authors: M. B. Malik, Khalid Munawar
    Abstract:

    This paper presents a low cost FPGA based solution for a real-time moving Object Tracking System. A specialized architecture is presented based on a soft RISC processor capable of running kernel based mean shift Tracking algorithm. The System includes a frame grabber unit that stores the video frame in DDR RAM using direct memory access, a video display unit to monitor the Tracking statistics and a soft processor capable of running mean shift Tracking algorithm within the required time constraint.

  • fpga soft processor based real time Object Tracking System
    Southern Conference Programmable Logic, 2009
    Co-Authors: M. B. Malik, Khalid Munawar
    Abstract:

    This paper presents a low cost FPGA based solution for a real-time moving Object Tracking System. A specialized architecture is presented based on a soft RISC processor capable of running kernel based mean shift Tracking algorithm. The System includes a frame grabber unit that stores the video frame in DDR RAM using direct memory access, a video display unit to monitor the Tracking statistics and a soft processor capable of running mean shift Tracking algorithm within the required time constraint.