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the coordinate system in this transformation. In Android, the default view coordinate system is the upper-left vertex (0, 0), the x-axis, and the y-axis. This requires that the rect coordinate be transformed. Another difficulty is that this face detection must be started after the camera is turned on, and if you take a photo or stop the preview, you need to activate it again. You need to add a delay when a
This is an introduction to the face detection of technology from the view of the article:
"2016 ACM MM unitbox:an Advanced Object Detection Network".
The code should not be put out, but the implementation is relatively simple. (Interrupt a sentence, the paper said speed can reach 12fps, I'm a little panic, we look at science does not) —————————— split line ——————
This article is reproduced from: https://blog.csdn.net/shuzfan/article/details/52625449
This is an introduction to the face detection of technology from the view of the article:
"2016 ACM MM unitbox:an Advanced Object Detection Network".
The code should not be put out, but the implementation is relatively simple. (Interrupt a sentence, the paper said speed can re
Original:
http://blog.csdn.net/marvin521/article/details/11489453
04. Application Example of probability graph model
A recent article "Deformable Model Fitting by regularized Landmark Mean-shift" in the Human Face detection algorithm in the speed and precision of the compromise reached a relatively good level, This technical report will explain the working pr
color area can be implemented using the following rules:
Reference Papers of the above algorithms: Adaptive Skin Color modeling using the skin locus.pdf
A novel method for detecting lips, eyes and faces in real time
Articles related to Baidu Library: A Rapid face detection algorithm based on the mixed skin color model
In the preceding formula, lowercase R, G, a
One of the target detection (traditional algorithm and deep learning source learning)
This series of writing about target detection, including traditional algorithms and in-depth learning methods will involve, focus on the experiment and not focus on the theory, theory-related to see the paper, mainly rely on OPENCV.
First, what is the target
In many cases the need for efficient skin tone detection code, I commonly used a C + + version of the code as follows:voidIm_getroughskinregion (unsignedChar*SRC, unsignedChar*skin,intWidth,intHeight,intStride) { for(intY =0; Y ) {unsignedChar*lineps = SRC + Y * Stride;//The first address of the Y-line pixel of the source graphUnsignedChar*LINEPD = Skin + Y * Width;//the first address of the Y-line pixel of the skin area for (int X = 0; X
The research of image feature detection has been a long time, many methods of image feature detection, coupled with the deformation of various algorithms, it is difficult to fully understand in a short period of time, but the main feature detection algorithm principle of the study. Overall, image features can include c
viola-jones human eye detection algorithm +meanshift tracking algorithmThis time the code is the video of the human eye part of the detection and tracking, testing using MATLAB comes with the human eye Detection ToolboxHere are some things that the MATLAB website describes this algorithm:Http://cn.mathworks.com/help/vi
First, Background introductionSkin detection has been widely used in many computer applications such as face recognition and tracking, gesture recognition, image retrieval and classification. The above research topics must solve a fundamental problem, that is, the image is precisely divided into two areas of the skin and background, the accuracy of the division is directly affecting the precision and perfor
With the rise of artificial intelligence, target detection algorithm plays a more and more important role in various industries, how to land, this is a very serious topic. Today I saw a Daniel share, study.To comb the algorithm and history of this field. Facilitate follow-up studies.According to the time classification, the a
viewpoints are put forward for the optimization of the vehicle detection algorithm of this kind of scanning mechanism.
First of all, make some summary of this article. The combination of Haar feature and AdaBoost classification algorithm is first used for face detection, th
IntroductionIn the previous section, I described how to implement a ray-to-triangle cross-detection algorithm. However, we should know that in game development, a model has a lot of triangles, if you want to all objects, all the triangles to do this detection, even if the current computer computing ability, is not efficient to complete. Therefore, we need to use
?? Recently, when solving three-dimensional problems, it is necessary to judge whether the segment crosses the cube, and the question can be extended as follows: whether the ray passes through the cube aabb.?? The commonly used algorithm for collision detection in 3D game development is the axis-aligned rectangular bounding box (axially Aligned bounding box, AABB) box method, the basic idea is to use a cube
will repeat the detection for the same target. We use non-maxima suppression to remove a low-confidence duplicate detection. Rank predictions from highest to lowest in confidence. If any of the predictions are of the same category as the current forecast and the two IoU are greater than 0.5, we will remove them from this sequence.Focal Loss (retinanet)Category imbalance can compromise performance. SSDs Res
This article involves a lot of algorithms, there are many similar articles on the network, but it is certain that many are not worthy of code, or the accompanying code are symbolic, slow, not elegant, not practical value, this article tries to solve these problems.The order of each algorithm in this paper does not represent the superiority of the algorithm, but only the random arrangement of the authors.2.
Author: gnuhpcSource: http://www.cnblogs.com/gnuhpc/
The target detection method was initially proposed by Paul Viola [vila01] and improved by Rainer lienhart [lienhart02. first, a cascade boosted classifier is obtained by training the classifier using the Harr feature of the sample (about several hundred sample images. The training samples are divided into positive samples and inverse samples. The positive samples refer to the target samples to be ch
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