Description: 本文对视频运动目标跟踪算法进行研究。在视频运动目标的提取中，介绍常用的图像差分算法、光流算法和主动轮廓模型算法。-In this paper, the video moving target tracking algorithm study. Video moving target in the extraction, the introduction of images commonly used differential algorithm, optical flow algorithm and active contour model algorithm. Platform: |
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Author:于晓辉 |
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Description: mean shift 目标跟踪，用于跟踪视频目标，本人修改了部分程序。均值转移算法、均值转移代码、Mean-Shift，用于视觉目标跟踪、视频监控、主动视觉等领域，还可以用于图像分割/图像聚类/聚类分割。-mean shift algorithm is used to track visual object. Applied in visual object tracking, visual tracking, visual surveillance and active vision. Platform: |
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Author:朱亮亮 |
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Description: snake 模型的MATLAB算法。可用于图形轮廓识别等图像处理方面的领域。-active contour model developed by others.It can be used in line detection and motion tracking.If someone wants to use it,please get in tough with the developer. Platform: |
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Description: 该代码用于实现粒子滤波视觉目标跟踪(PF)、卡尔曼粒子滤波视觉目标跟踪(KPF)、无迹粒子滤波视觉目标跟踪(UPF)。它们是本人这两年来编写的核心代码，用于实现鲁棒的视觉目标跟踪，其鲁棒性远远超越MeanShift(均值转移)和Camshift之类。用于实现视觉目标跟踪的KPF和UPF都是本人花费精力完成，大家在网上是找不到相关代码的。这些代码虽然只做了部分代码优化，但其优化版本已经成功应用于我们研究组研发的主动视觉目标跟踪打击平台中。现在把它们奉献给大家！-These codes are used to realize particle filter based visual object tracking (PF), kalman particle filter based visual object tracking, unscented particle filter based visual object tracking. Their robustness is far beyond the classical visual object tracking algorithms such as Mean-Shift (MeanShift) and CamShift。The codes of KPF and UPF for visual object tracking cost a great of my energy, and you can not find any relating algorithm codes on internet! Our research group have optimized these codes and applied them to develop a platform for active visual object tracking. Now, I dedicate them to you and wish you love them! Platform: |
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Author:朱亮亮 |
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Description: 这是一个针对采用三相三线制有源电力滤波器的matlab仿真model，采用一种带积分的位置跟踪滑模控制方法，实现电源电流的追踪控制。-This is a simulation model for the three-phase three-wire active power filter matlab, using a position tracking with integral sliding mode control method to achieve supply current tracking control. Platform: |
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Description: 人脸检测与跟踪是一个重要而活跃的研究领域，它在视频监控、生物特征识别、视频编码等领域有着广泛的应用前景。该项目的目标是在FPGA板上实现实时系统来检测和跟踪人脸。人脸检测算法包括肤色分割和图像滤波。通过计算被检测区域的质心来确定人脸的位置。该算法的软件版本独立实现，并在matlab的静止图像上进行测试。虽然从MATLAB到Verilog的转换没有预期的那样顺利，实验结果证明了实时系统的准确性和有效性，甚至在不同的光线、面部姿态和肤色的条件下也是如此。所有硬件实现的计算都是以最小的计算量实时完成的，因此适合于功率受限的应用。(Face detection and tracking is an important and active research field, and it has a wide range of applications in video surveillance, biometrics, video coding and other fields. The goal of the project is to implement real-time systems on the FPGA board to detect and track faces. Face detection algorithms include skin segmentation and image filtering. The location of the human face is determined by calculating the centroid of the detected region. The software version of the algorithm is implemented independently and tested on MATLAB still images. Although the conversion from MATLAB to Verilog is not as smooth as expected, the experimental results demonstrate the accuracy and effectiveness of real-time systems, even in different light, facial gestures and color conditions. All hardware implementations are performed in real-time with minimal computational complexity and are therefore suitable for power constrained applications.) Platform: |
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Author:合发
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