Description: The first step to intelligent image/video processing for face recognition in uncontrolled scenery with complex backgrounds (outdoor environments, airports, train/bus stations) is face detection. The precision of the latter heavily depends your face recognition results. Typically scientists investigating in that field do not have the time or the ability to develop optimized C++ code ready for commercial use and confine themselves with the Matlab development process only. Platform: |
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Author:曲亚武 |
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Description: Abstract: Effective data processing is required with the fast development of multimedia technology. Compressed-domain images/video processing techniques have captured the attention of many researchers in recent years, and research on face detection and tracking in compressed-domain video becomes a new trend. Based on the analysis of the background and research status, some important future directions are presented.
Key words: face detection；face tracking；compressed domain -Abstract : Effective data processing is required with the fast development of multimedia technology. Co. mpressed-domain images/video processing Edge (have captured the attention of many res earchers in recent years, and research on face detection and tracking in c Item-domain video becomes a new trend. Ba sed on the analysis of the background and resear ch status, some important future directions are presente d. Key words : face detection; face tracking; compressed domain Platform: |
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Author:黄永 |
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Description: The first step to intelligent image/video processing for face recognition in uncontrolled scenery with complex backgrounds (outdoor environments, airports, train/bus stations) is face detection. The precision of the latter heavily depends your face recognition results. Typically scientists investigating in that field do not have the time or the ability to develop optimized C++ code ready for commercial use and confine themselves with the Matlab development process only. -The first step to intelligent image/video processing for face recognition in uncontrolled scenery with complex backgrounds (outdoor environments, airports, train/bus stations) is face detection. The precision of the latter heavily depends your face recognition results. Typically scientists investigating in that field do not have the time or the ability to develop optimized C++ code ready for commercial use and confine themselves with the Matlab development process only. Platform: |
Size: 194560 |
Author:曲亚武 |
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Description: 都是用matlab写的，复制到txt上了
（1）基于简单背景的人脸监测，针对视频，效果还不错，传的是txt，大家新建一个M文件，复制，然后把视频名与程序中的改成一致就可以了。
（2）对多椭圆的检测，非实际图像，无噪声，就是简单的椭圆，使用同上。-Are written with matlab, copy to the txt on the (1) human face based on a simple background monitoring, for video, the results were good, communication is the txt, you create a new M file, copy, and then the video name and program The change in line on it. (2) the detection of multi-elliptical, non-real image, no noise, that is a simple oval, use ibid. Platform: |
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Author:sss |
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Description: 智能图像/视频处理中，复杂背景环境（比如室外环境、机场、车站等）下，人脸识别的第一步是人脸的检测。它的精确度直接影响到后期识别的结果。不过，领域内的科学家们基本上很难有足够的精力和时间开发优化的C++代码，使其用于商业用途，而一般都是只在Matlab中进行模拟。
本文的目的是提供一个我开发的SSE优化的，C++库，用于人脸检测，你可以马上把它用于你的视频监控系统中。文章中的分类器的训练数据来自与我的 webcam图像，它们被采集于不同时间，不同光照，不同背景环境下，它几乎可以实时地检测出我（的脸：）。训练的非人脸数据来自对不同背景的采集，用的是同一个webcam。被提取出的人脸区域，已经经过下面的处理：高斯滤波，直方图均衡化。
如果你需要更精确的结果，请从internet上下载更多不同的人脸集合，然后从新训练分类器。和我的库中一样尺寸的公共库是CBCL，其库超过100MB，所以，请大家自己下载楼-Intelligent image/video processing, complex background environment (such as an outdoor environment, airports, stations, etc.), the first step is the recognition of face detection. It directly affects the accuracy of the latter part of the identification results. However, scientists in the field are basically difficult to have enough energy and time to develop optimized C++ code to be used for commercial purposes, and are generally only be simulated in Matlab. The purpose of this paper is to provide an optimized SSE my development, C++ library for face detection, you can immediately use it for your video surveillance system. Face article classifier training data with my webcam images, which are collected at different times, in different lighting, different background environment, it is almost real-time detection of me (a :). Training of non-face data collection different backgrounds, with the same webcam. Was extracted face region, has been subjected to the following treatment: Gaussi Platform: |
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Author:周文活 |
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Description: This project investigates the blink behavior and other eye movements related with
automobile driver during long time driving. The main aim is to map certain events in a
recorded electro-oculogram (EOG) to actual blink behavior as measured via video of the
drivers face. Based on the obtained knowledge, it will be possible to improve the detection
method for driver’s eyelid blink and to develop more robust measures of the driver’s
drowsiness state. Platform: |
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Author:Muhammad Chowdhury |
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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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Description: Matlab火焰烟雾检测(GUI)
本设计为基于matlab的烟雾火焰火灾识别系统，可读取视频或者图象，检测出是否有烟雾火焰，具备一个人机交互式GUI界面，功能强大，识别准确，同时配备相对应的操作说明和运行效果图，直接运行GUI文件即可完美运行。另外，诸如车牌，人脸，图象去雾，压缩，水印，疲劳检测，人数统计，声音信号处理等均可做技术交琉，欢迎一起探讨。(Matlab flame smoke detection (GUI)
This design is a smoke and flame fire recognition system based on MATLAB. It can read video or image, detect whether there is smoke and flame. It has an interactive GUI interface with powerful function and accurate recognition. At the same time, it is equipped with corresponding operation instructions and operation effect diagram. Running GUI file directly can run perfectly. In addition, such as license plate, face, image defogging, compression, watermark, fatigue detection, number of people statistics, sound signal processing, etc. can do technology jiaoryu, welcome to discuss together.) Platform: |
Size: 12152832 |
Author:for Matlab |
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Search - video face detection with matlab