Terrain depth estimation and disparity map extraction for aerial images using Stereovision

The purpose of this project is to estimate terrain depth and disparity map generation using aerial images with the help of stereovision techniques. One of the important problems in stereovision is stereo matching in aerial images is to calculate the Digital Elevation Model (DEM). The Main purpose of stereovision is to determine object disparity or [...]

By | May 18th, 2017|Uncategorized|0 Comments

Camera pose estimation in a sequence of monocular images

Estimating camera pose parameters and constructing robust and accurate map in a sequence of monocular images is a challenging task in computer vision and robotic applications. It is in close relationship with some fundamental problems in computer vision, e.g., 3D reconstruction, image registration and feature matching. Simultaneous Localization and Mapping (SLAM) and Augmented Reality (AR) [...]

By | May 13th, 2017|Uncategorized|0 Comments

Design and Implementation of Rotary Wing UAVs Stabilizer

Vertical flying machines such as quadrotors and drones are becoming more and more popular in different aspects of life such as medical emergencies and aerial imaging. Such devices are easy to design and inexpensive to maintain but despite of these great features and its simplicity, quadrotors are unstable in nature and require constant stabilization and [...]

By | March 11th, 2017|Uncategorized|0 Comments

Extracting Disparity Map from Aerial Images by Stereo Vision

The goal of this project is to extract the 3rd dimension of a scene using stereo vision. Stereo vision uses two images taken from different angles to obtain the lost dimension during photography. Many approaches proposed for this problem. In this project two of them have been implemented: coarse to fine block matching and dynamic programming. Most of the stereo vision approaches have a comparison algorithm that estimate the similarity of two small regions, one from the left image and the other from the right image. The common comparison algorithm is sum of squared differences for each pixel of those regions. In this project two new comparison algorithms are proposed, similarity estimation in striped binary images (SESBI) and binary subtraction. […]

By | March 11th, 2017|Uncategorized|0 Comments