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: |
Size: 145408 |
Author:黄永 |
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Description: 特征跟踪源码，包括FeatureTracker.cpp和FeatureTracker.h，其中另附有边缘检测和人脸检测源码，调用了blepo.lib。-feature tracking source, FeatureTracker.cpp and FeatureTracker.h including, which followed by edge detection and face detection source, call the blepo.lib. Platform: |
Size: 4096 |
Author:ppcc |
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Description: 人脸检测及跟踪是属于计算机视觉与模式识别研究领域的一个重要分支，它作为人脸信息处理中的一项关键技术，在基于内容的图像与视频检索、视频监控与跟踪、视频会议以及智能人机交互等方面都有着重要的应用价值。-Face detection and tracking is a computer vision and pattern recognition research area an important branch of facial information as a key deal with technology, content-based image and video retrieval, video surveillance and tracking, video conferencing and intelligent areas such as human-computer interaction have important application value. Platform: |
Size: 5865472 |
Author:阳关 |
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Description: 实时视频图像中的人脸检测与跟踪,适合做毕业设计的同学用做参考资料-Real-time video images of human face detection and tracking, designed for graduate students to do make reference to use Platform: |
Size: 585728 |
Author:冉艺琚 |
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Description: 用visual c++开发的人脸检测示例程序，实现人脸定位与跟踪-Using visual c++ Developed examples of face detection process, the realization of Face Locating and Tracking Platform: |
Size: 5477376 |
Author:sue_Langsujuan |
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Description: 人脸检测和跟踪学位论文；人脸检测定位：运动区域检测预处理， 肤色区域的分割和利用二值形态学等操作的人脸粗检，利用眼、嘴特征的彩色信息检测的人脸细检，利用投影法检测眼睛和嘴巴亮块的人脸定位。提出了一种基于自适应肤色模型匹配与验证的方法对人脸进行跟踪-Face detection and tracking dissertation Face Detection positioning: Sports regional detection pretreatment, color region segmentation and the use of binary morphological operations, such as human faces rough seizure, the use of eyes, mouth features detection of color information Face Fine Frederick, using projection method bright eyes and mouth block face positioning. A model based on adaptive color matching and validation of the method of face tracking Platform: |
Size: 3622912 |
Author:田卉 |
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Description: This file helps identify the presence of a human face, hand or any other body part by identifying and marking skin-like pixels within a given image. With further image processing techniques, the output produced by this script can be refined and processed to be fed into larger face detection and tracking, gesture recognition, and other HCI applications. Platform: |
Size: 403456 |
Author:Hamlin DSouza |
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Description: Robust Real-Time Eye Detection and
Tracking Under Variable Lighting Conditions
and Various Face Orientations Platform: |
Size: 963584 |
Author:betra |
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Description: Face detection algorithms are widely used in computer vision as they provide fast and reliable results depending on the application
domain. A multi view approach is here presented to detect frontal and profile pose of people face using Histogram of Oriented Gradients, i.e. HOG, features. A K-mean clustering technique is used in a cascade of HOG feature classifiers to detect faces. The evaluation of the algorithm shows similar performance in terms of detection rate as state of the art algorithms. Moreover, unlike state of the art algorithms,our system can be quickly trained before detection is possible. Performance is considerably increased in terms of lower computational cost and lower false detection rate when combined with motion constraint given by moving objects in video sequences. The detected HOG features are integrated within a tracking framework and allow reliable face tracking results in several tested surveillance video sequences. Platform: |
Size: 293888 |
Author:linuszhao |
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Description: 基于adaboost和mean-shift视频中的人脸检测与跟踪识别-face detection and tracking recognition
of videoBased on adaboost and mean-shift Platform: |
Size: 5272576 |
Author:jianghui |
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Description: 基于AdaBoost和mean-shift视频中的人脸检测与跟踪识别-Based on AdaBoost and mean-shift video of face detection and tracking recognition Platform: |
Size: 18119680 |
Author:jianghui |
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Description: 本文运用haar特征分类，对人脸进行动态的检测和跟踪，经过试验对比可以发现效果很好，识别率较高-This paper uses haar feature classification, human face detection and tracking of dynamic, contrast can be found through the test with good results, the recognition rate is higher Platform: |
Size: 5889024 |
Author:张万贺 |
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Description: Object detection and tracking are important in many computer vision applications including activity recognition, automotive saf ety,
and surveillance. In this example, you w ill develop a simple f ace tracking system by dividing the tracking problem into three
separate problems:
1. Detect a f ace to track
2. Identif y f acial f eatures to track
3. Track the f ace Platform: |
Size: 887808 |
Author:Nurita |
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Description: This thesis proposes a novel algorithm for integrated face detection and face tracking
based on the synthesis of an adaptive particle filtering algorithm and an AdaBoost face detection
algorithm. A novel Adaptive Particle Filter (APF), based on a new sampling technique, is
proposed to obtain accurate estimation of the proposal distribution and the posterior distribution
for accurate tracking in video sequences. The proposed scheme, termed a Boosted Adaptive
Particle Filter (BAPF), combines the APF with the AdaBoost algorithm. The AdaBoost
algorithm is used to detect faces in input image frames, while the APF algorithm is designed to
track faces in video sequences. The proposed BAPF algorithm is employed for face detection,
face verification, and face tracking in video sequences. Experimental results confirm that the
proposed BAPF algorithm provides a means for robust face detection and accurate face tracking
under various tracking scenarios. Platform: |
Size: 1057792 |
Author:Trabelsi |
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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: |
Size: 63488 |
Author:合发
|
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