Description: 自已写的Adaboost使用Haalike feature，去Detection-Adaboost use their own written Haalike feature, to Detection Platform: |
Size: 9216 |
Author:博邻 |
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Description: Matlab脸部识别程序包括
haar feature
adaboosting-Matlab including facial recognition program haar featureadaboosting Platform: |
Size: 1809408 |
Author:Roger |
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Description: A very fast and robust object detection
framework.
A very simple set of Haar like box features
A commensurating Image representation (that
enables fast calculation of features, feature
scaling and normalization)
Efficient feature selection based on boosting
Attentional Cascading of classifiers that spends
more time on promising regions. Platform: |
Size: 161792 |
Author:jinwoosmile |
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Description: Haar-Like Feature臉部辨識程式及源代碼,是研究快速臉部辨識的好例程-Haar-Like Feature facial recognition programs and source code, is to study the fast face recognition in a good routine Platform: |
Size: 199680 |
Author:賴永成 |
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Description: 人脸检测代码Adaboost实现Haar feature积分图像-Human face detection using adaboost with haar-like feature and integral image. Platform: |
Size: 491520 |
Author:machunfei |
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Description: This project focuses on calculating the similarity between the images using genetic algorithm and haar-wavelet. Haar wavelet is being used in order to calculate the images with different features like various expressions or gloomy or other characteristics.
This system extracts the feature from images by wavelet transform, and provides a user-friendly means to retrieve an image from a large database when the user cannot clearly define what the image must be. Platform: |
Size: 865280 |
Author:harshit |
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Description: Very recently tracking was approached using classification techniques such
as support vector machines. The object to be tracked is discriminated by a
classifier from the background. In a similar spirit we propose a novel on-line
AdaBoost feature selection algorithm for tracking. The distinct advantage of
our method is its capability of on-line training. This allows to adapt the classifier while tracking the object. Therefore appearance changes of the object
(e.g. out of plane rotations, illumination changes) are handled quite naturally.
Moreover, depending on the background the algorithm selects the most discriminating features for tracking resulting in stable tracking results. By using
fast computable features (e.g. Haar-like wavelets, orientation histograms, local binary patterns) the algorithm runs in real-time. We demonstrate the performance of the algorithm on several (publically available) video sequences. Platform: |
Size: 327680 |
Author:lili |
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Description: 通过改进基于Haar-like特征和Adaboost的级联分类器，提出一种融合Haar-like特征和
HOG特征的道路车辆检测方法-By improving based on Haar-like features and Adaboost cascade classifier, presents a fusion of Haar-like features and characteristics of HOG road vehicle detection method Platform: |
Size: 951296 |
Author:hengluo |
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Description: this is fpga BASED HAAR like feature for face detection
it s include algorithms and explanations of haar features
-this is fpga BASED HAAR like feature for face detection
it s include algorithms and explanations of haar features
Platform: |
Size: 640000 |
Author:saif king |
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Description: 本程序实现选定图像的Haar-like特征提取功能，方便学习者能直观的看到各类Haar-like特征值。代码简单易于理解。-The program implements the selected image Haar-like feature extraction function to facilitate the learners can visually see all kinds of Haar-like feature values. Code is simple and easy to understand. Platform: |
Size: 2048 |
Author:roy |
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Description: SURF意指 加速的具有鲁棒性的特征，由Bay在2006年首次提出，这项技术可以应用于计算机视觉的物体识别以及3D重构中。SURF算子由SIFT算子改进而来，一般来说，标准的SURF算子比SIFT算子快好几倍，并且在多幅图片下具有更好的鲁棒性。SURF最大的特征在于采用了harr特征以及积分图像integral image的概念，这大大加快了程序的运行时间。-SURF (Speeded Up Robust Feature) is a robust local feature detector, first presented by Herbert Bay et al. in 2006, that can be used in computer vision tasks like object recognition or 3D reconstruction. It is partly inspired by the SIFT descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. SURF is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images.
Platform: |
Size: 2418688 |
Author:草 |
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Description: Haar-like特征遍历，并求取不同特征在24*24图片下的特征个数-Haar-like feature traversal, and obtains the number of different features in the feature image of 24* 24 Platform: |
Size: 1024 |
Author:wangzr |
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Search - haar like feature