# Image Processing

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## Human detection and Pose Estimation with Deep Learning for Sport Analysis

Pose estimation and tracking human is one the key step in sports analysis. Here is in this work I used openpose for analysis of player in a Bundesliga game HSV Hamburg vs Bayer München. Warning: the video might be disturbing for HSV fans 🙂   Original Video Analyzed Video Original Video Analyzed Video Original Video Analyzed Video Original Video

## RGBD PCL point cloud from Stereo vision with ROS and OpenCV

In my other tutorial, I showed you how to calibrate you stereo camera. After Calibration, we can get disparity map and  RGBD PCL point cloud from our stereo camera cool huh 🙂 1)Save the following text under “stereo_usb_cam_stream_publisher.launch”

2) Then run the following node to publish both cameras and camera info (calibration matrix)

3) Run the

## Stereo Camera Calibration with ROS and OpenCV

In this tutorial, I’m gonna show you stereo camera calibration with ROS and OpenCV. So you need a pair of cameras, I bought a pair of this USB webcam which is okay for this task. 1)Save the following text under “stereo_usb_cam_stream_publisher.launch”

2)Then run the following node to publish both cameras.

3)Now call the calibration node:

## Open source Structure-from-Motion and Multi-View Stereo tools with C++

Structure-from-Motion (SFM) is genuinely an interesting topic in computer vision, Basically making 3D structure from something 2D is absolutely mesmerizing 🙂 There two open source yet very robust tools for SFM, which sometimes compiling them might be complicated, here I will share my experience with you. 1)VisualSFM Prerequisite: 1)Glew Download the glew from SF at http://glew.sourceforge.net/. Do NOT get it from Github as

## Finding Homography Matrix using Singular-value Decomposition and RANSAC in OpenCV and Matlab

Solving a Homography problem leads to solving a set of homogeneous linear equations such below: \left( \begin{array}{ccccccccc} -x1 & -y1 & -1 & 0 & 0 & 0 & x1*xp1 & y1*xp1 & xp1\\ 0 & 0 & 0 & -x1 & -y1 & -1 & x1*yp1 & y1*yp1 &  yp1\\ -x2 & -y2 &

## Finding Affine Transform with Linear Least Squares

linear least squares is a method of fitting a model to data in which the relation between data and unknown paramere can be expressed in a linear form. $$Ax=b$$ $$X^{*}= \underset{x}{\mathrm{argmin}}= \|Ax-b\|^{2} =(A^{T}A)^{-1}A^{T}b$$

And testing the code:

## Peak Signal-to-Noise Ratio (PSNR) in Image using OpenCV and Matlab

Peak signal-to-noise ratio (PSNR) shows the ratio between the maximum possible power of a signal and the power of the same image with noise. PSNR is usually expressed in logarithmic decibel scale. $$MSE =1/m*n \sum_{i=0}^{m-1} \sum_{j=0}^{n-1} [ Image( i,j) -NoisyImage( i,j) ] ^2$$ $$PSNR =10* \log_{10} \Bigg(MAXI^2/MSE\Bigg)$$ MSE is Mean Square Error and MAXI is

## Seam Carving Algorithm for Content-Aware Image Resizing with Matlab Code

Seam carving is an algorithm for resizing images while keeping the most prominent and conspicuous pixels in the image. The important pixels in an image are usually those who are located over horizontal or vertical edges, so to throw away some pixels we first find horizontal and vertical edges and store their magnitude as pixel