computer-vision

问题 I'm trying to transform a static image to give the illusion of it being taken from different angles. It seems like warpPerspective and warpAffine are the functions I should understand to make this work. However, even after read the OpenCV docs, I'm having difficulty understanding them. What tutorials/docs should I read that explain them very well? 回答1: warpPerspective does a projective transformation or homography: http://en.wikipedia.org/wiki/Homography warpAffine does an affine

问题 I'm trying to transform a static image to give the illusion of it being taken from different angles. It seems like warpPerspective and warpAffine are the functions I should understand to make this work. However, even after read the OpenCV docs, I'm having difficulty understanding them. What tutorials/docs should I read that explain them very well? 回答1: warpPerspective does a projective transformation or homography: http://en.wikipedia.org/wiki/Homography warpAffine does an affine

问题 I hame some image with plane which have perspective transform. I need to detect center of each white rhombus or rhombus itself. Here is examples: As I unserstand the problem can be solved by simple template matching if we rectify image, but I need to do it automatically. Is there any functions in OpenCV suitable for this task? Any other ideas? 回答1: Here are two quick tests I just did without correcting the perspective issue. Pure mathematical morphology : Extract the red channel Big white top

问题 I'm working on a commercial product where I need to estimate the 6DOF pose of a known 3D CAD (closed 2-manifold triangular mesh) in a single 2D image. In general, this a difficult problem but under our operational conditions, we can impose the following constraints simplifying the problem: The CAD object is known and we do NOT aim for generality like recognizing the class of all chairs. We could get the user to position the camera approximately to a specific pose (distance from the object,

问题 I'm working on a commercial product where I need to estimate the 6DOF pose of a known 3D CAD (closed 2-manifold triangular mesh) in a single 2D image. In general, this a difficult problem but under our operational conditions, we can impose the following constraints simplifying the problem: The CAD object is known and we do NOT aim for generality like recognizing the class of all chairs. We could get the user to position the camera approximately to a specific pose (distance from the object,

问题 I am new to machine learning and currently working on a project. The project is about classifying images based on feature and color attributes. I have tried classifying images through feature extraction based on the example given in the OpenCV with Python by Example book (the Dense extractor SIFT descriptor technique to generate a codebook and train SVM to classify the extracted feature) but I haven't tried yet combining both feature and color attributes since the images sampled were gray

问题 I am new to machine learning and currently working on a project. The project is about classifying images based on feature and color attributes. I have tried classifying images through feature extraction based on the example given in the OpenCV with Python by Example book (the Dense extractor SIFT descriptor technique to generate a codebook and train SVM to classify the extracted feature) but I haven't tried yet combining both feature and color attributes since the images sampled were gray

问题 IBM Watson has a capability where you can train the classifiers on Watson using your images but I am unable to find a similar capability on Google Cloud Vision API? What I want is that I upload 10-15 classes of images and on the bases of upload images classify any images loaded after that. IBM Bluemix (Watson) has this capability but their pricing is significantly higher than Google. I am open to other services as well, if prices ares below Google's 回答1: As far as I know Google Cloud Vision

问题 IBM Watson has a capability where you can train the classifiers on Watson using your images but I am unable to find a similar capability on Google Cloud Vision API? What I want is that I upload 10-15 classes of images and on the bases of upload images classify any images loaded after that. IBM Bluemix (Watson) has this capability but their pricing is significantly higher than Google. I am open to other services as well, if prices ares below Google's 回答1: As far as I know Google Cloud Vision

问题 I have run the face detection algorithm inbuilt in opencv to extract faces in each frame of a video(sampled at 1 fps). I have also resized each face image to be of same size and I have cropped some fraction of image to remove background noise and hair. Now the problem is that I have to cluster these images of faces - Each cluster corresponding to a person. I implemented the algorithm described here http://bitsearch.blogspot.in/2013/02/unsupervised-face-clustering-with-opencv.html Basically