pose-estimation

问题 I am using the tflite model for posenet from here. It takes input 1*353*257*3 input image and returns 4 arrays of dimens 1*23*17*17, 1*23*17*34, 1*23*17*64 and 1*23*17*1. The model has an output stride of 16. How can I get the coordinates of all 17 pose points on my input image? I have tried printing the confidence scores from the heatmap of out1 array but I get near to 0.00 values for each pixel. Code is given below: public class MainActivity extends AppCompatActivity { private static final

问题 I'm using "OpenCV for Unity3d" asset (it's the same OpenCV package for Java but translated to C# for Unity3d) in order to create an Augmented Reality application for my MSc Thesis (Computer Science). So far, I'm able to detect an object from video frames using ORB feature detector and also I can find the 3D-to-2D relation using OpenCV's SolvePnP method (I did the camera calibration as well). From that method I'm getting the Translation and Rotation vectors. The problem occurs at the

问题 I am looking into the tensorflow implementation of posenet to do pose estimation in real time and also if possible in an offline mode. I am looking into the following repo : https://github.com/tensorflow/tfjs-models/tree/master/posenet The keypoints are read out in the following function in the following section of code export function drawKeypoints(keypoints, minConfidence, ctx, scale = 1) { for (let i = 0; i < keypoints.length; i++) { const keypoint = keypoints[i]; if (keypoint.score <

问题 Can anyone know what is going on with this opencv error ? cv2.error: /home/desktop/OpenCV/opencv/modules/core/src/matrix.cpp:2294: error: (-215) d == 2 && (sizes[0] == 1 || sizes[1] == 1 || sizes[0]*sizes[1] == 0) in function create Line code which raise it is : rvecs, tvecs, inliers = cv2.solvePnPRansac(objp, corners2, cameraMatrix, dist) I followed step by step this tutorial: http://docs.opencv.org/master/dc/dbb/tutorial_py_calibration.html It seems that cameraMatrix is incorrect, but why ?

问题 I am trying to estimate the pose of a camera by scanning two images taken from it, detecting features in the images, matching them, creating the fundamental matrix, using the camera intrinsics to calculate the essential matrix and then decompose it to find the Rotation and Translation. Here is the matlab code: I1 = rgb2gray(imread('1.png')); I2 = rgb2gray(imread('2.png')); points1 = detectSURFFeatures(I1); points2 = detectSURFFeatures(I2); points1 = points1.selectStrongest(40); points2 =

问题 I am trying to get a global pose estimate from an image of four fiducials with known global positions using my webcam. I have checked many stackexchange questions and a few papers and I cannot seem to get a a correct solution. The position numbers I do get out are repeatable but in no way linearly proportional to camera movement. FYI I am using C++ OpenCV 2.1. At this link is pictured my coordinate systems and the test data used below. % Input to solvePnP(): imagePoints = [ 481, 831; % [x, y]

问题 I am doing camera calibration from tsai algo. I got intrensic and extrinsic matrix, but how can I reconstruct the 3D coordinates from that inormation? 1) I can use Gaussian Elimination for find X,Y,Z,W and then points will be X/W , Y/W , Z/W as homogeneous system. 2) I can use the OpenCV documentation approach: as I know u , v , R , t , I can compute X,Y,Z . However both methods end up in different results that are not correct. What am I'm doing wrong? 回答1: If you got extrinsic parameters

问题 I am doing camera calibration from tsai algo. I got intrensic and extrinsic matrix, but how can I reconstruct the 3D coordinates from that inormation? 1) I can use Gaussian Elimination for find X,Y,Z,W and then points will be X/W , Y/W , Z/W as homogeneous system. 2) I can use the OpenCV documentation approach: as I know u , v , R , t , I can compute X,Y,Z . However both methods end up in different results that are not correct. What am I'm doing wrong? 回答1: If you got extrinsic parameters

问题 I want to augment a virtual object at x,y,z meters wrt camera. OpenCV has camera calibration functions but I don't understand how exactly I can give coordinates in meters I tried simulating a Camera in Unity but don't get expected result. I set the projection matrix as follows and create a unit cube at z = 2.415 + 0.5 . Where 2.415 is the distance between the eye and the projection plane (Pinhole camera model) Since the cube's face is at the front clipping plane and it's dimension are unit

问题 I'm currently building a model on Tensorflow( ver:1.8 os:Ubuntu MATE16.04) platform. The model's purpose is to detect/match Keypoints of human body. While training, the error "No gradients for any variable" occurred, and I have difficulties to fix it. Background of the model : Its basic ideas came from these two papers: Deep Learning of Binary Hash Codes for fast Image Retrieval Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks They showed it's possible to match