hog silhouette

1, take the picture in the following slide as an example, I want to deduct the black frame part of the picture, but keep the silhouette of the black body in the moon. First, click the mouse to select the picture, switch to the Format tab under Picture Tools, and click the Delete Background button in the Adjustments feature group. 2, the presentation switch to the background removal tab. The purple area is the part of the image to be delet

If you do not have Photoshop beauty Mito and other image processing tools, how to quickly pull the map? Here is a small compilation to teach you how to use PPT2010 to pull the map. A PPT tutorial for quick PPT2010 in the middle of an image 1, take the picture in the following slide as an example, I want to deduct the black frame part of the picture, but keep the silhouette of the black body in the moon. First, click the mouse to select the picture,

(pencil tool) to draw a figure on the back of the outline sketch, height and step one of the two linear interval (12 mesh) is basically equal (Figure 03) Four, in the layer 2 of the fifth to draw a character back around 90 degrees of characters sideways outline sketch, height than the first detective figure slightly higher, 12 grid height fill (Figure 04) Five, in the 12th of the Layer 2 to draw a figure from the fifth to the

Although PPT is not a professional image processing tool, but it has a certain range of simple image processing capabilities. When we insert a picture to try to extract something extra to achieve something we want, or better fit into the slide background, we can use the "Remove background" feature of the PPT to pull the picture. Operation Steps Take the picture in the slide below as an example, I want to pull out the black frame part of the picture, but keep the

set the hierarchy[i][3]==-1 to mean "silhouette without parents", i.e. "this contour has no upper-class contour".Similarly, hierarchy[i][2]==-1 means "This contour does not have the first child", i.e. "this contour does not have the outline of the lower class".As for, hierarchy[][0],hierarchy[][1] refers to the latter contour of this contour, and the previous contour. They are the contours of the same class. This sequence may be very casual, and has

[1] Take the picture in the slide below as an example, I want to pull out the black frame part of the picture, but keep the silhouette of the black body in the moon. First, click the mouse to select the picture, switch to the Format tab under Picture Tools, and click the Delete Background button in the Adjustments feature group. [2] The presentation switches to the Background removal tab. The purple area is the part of the image to be del

Previously, we used MATLAB to implement algorithms. Recently, we started to use opencv as a target tracking algorithm. We found that opencv is really powerful. It integrates many algorithms and encapsulates many functions, the method is similar to MATLAB, but it is more efficient than Matlab. The following describes the human body detection code using the hog algorithm, which is similar to peopledetect. cpp in opencv. However, I modified some code to

Well-written SVM + hog Classifier Training Class mysvm: Public cvsvm {public: int get_alpha_count () {return this-> sv_total;} int get_sv_dim () {return this-> var_all;} int get_sv_count () {return this-> decision_func-> sv_count;} double * get_alpha () {return this-> decision_func-> alpha;} float ** get_sv () {return this-> Sv;} float get_rov () {return this-> decision_func-> rho;}}; void train () {char classifiersavepath [256] = "C: /pedestrianDete

Recently, we are working on Face Tracking Based on meanshift. The effect is average. The hue component is selected as the feature in the standard algorithm. To improve the robustness of the background, a multi-feature space is proposed based on features such as gradients and bps. However, the histogram dimension is too small and spatial information is lost, which seriously degrades the value of feature classification. After testing, the trace becomes invalid when the background color is similar

, older don't write, code directly call Vectorized way. Two_layer_net parameter Adjustment Features image related, hog and color histogram are all written for you. Other areas to look at the extraction features can not be used for reference, color histogram is a statistical feature. Hog seems to be the characteristics of statistics, statistics of the gradient in all directions to get the edge, not a

the bag of Features, characterized by the temporal and spatial characteristics of the bottom-up/low level, constantly updated with time and levels. The underlying object is detected by the template; Mid-level: The middle layer detects and tracks 2D skeleton pose from the images, and analyzes the dynamic pose through the background content; High-level: The high-level activity composition method is to combine the feature of different time points into a time-probability model. Temporal and

Let's focus on the parameters of the previous constructor, here are a few important parameters to study: Winsize (64,128), BlockSize (16,16), Blockstride (8,8), cellsize (8,8), Nbins ( 9). These are Hogdescriptor member variables, and the values in parentheses are their default values, which reflect the parameters of the hog descriptor. Here are a few to show what they mean.Gradient direction number NbinsNbins indicates the number of directions of the

Opencv handwritten multiple choice question marking (2) Character Recognition and opencv Character Recognition Opencv handwritten multiple choice question marking (2) Character Recognition Generally, you only need to identify ABCD and empty content for multiple-choice questions. In theory, the recognition rate is high. The recognition code references the online search code because there are many reference URLs, it's hard to figure out where the code is to be referenced, so I will not thank you h

, and then divides the imageKAnd Feature Representation is a real value obtained through the statistical ratio between directions. Both Haar-like and eohs can speed up the operation through the image integral graph method. Dalal and triggs [5] proposed histogram of Oriented Gradient (hog ). based on the gradient information, hog allows overlapping blocks. Therefore, it is not sensitive to illumination chang

1. the most famous is Ivan laptev's 3D Harris, which is an executable file that is easy to use. It is an extension of Harris's 3D space, after the feature points are detected, they are expressed by hog and HOF. The total feature dimension is 162 dimensions. Click here to go to the download page. 2. The cuboids corner detection method of P. Dollar is roughly filtered using 1D Gabor. After the corner points are detected, the author's experiment shows t

position filter Hf_den = (1-learning_rate) * Hf_den + learning_rate * New_hf_den; Hf_num = (1-learning_rate) * hf_num + learning_rate * new_hf_num; Understanding of SUM (hf_num. * XTF, 3) Examples can be tested as follows: >> A (:,:, 1) =[1 2;3 4]; >> A (:,:, 2) =[2 3;4 5]; >> B (:,:, 1) =[3 4;5 6]; >> B (:,:, 2) =[4 5;6 7]; >> sum (A. * b,3) ans = 59 Because 1*3+2*4=11 2*4+3*5=23 3*5+4*6=39 4*6+5*7=59So sum (A. * b,3) =a (i,j,1) *b (i,j,1) +a (i,j,2) *b (i,j,2). This can be seen as a and

ArticleDirectory Begisline Sphere subdivision Object silhouette Shader Model 4 brings us the geometry shader. In fact, this thing already exists in some 3D animation production software, such as Maya 8. I took a look at which preview and csustan.edu of dx10 used to show you the usage and features of geometry shader. To be honest, there is really little information about this geometry shader, and there are only a few thin lines on

We will give you a detailed analysis of photoshop software and share with you the post-processing tutorial on combining multiple photos with one multi-portrait photo.Tutorial sharing:Many people are curious about how to take a photo. Some people say that it is not so complicated to erase layers. Today we will teach you how to combine multiple silhouette portraits in one step.However, this method only applies to si