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Visual Odometry

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Overview

Visual Odometry is a subfield of computer vision where we aim to estimate the egomotion of an agent through camera images. In this project monocular images from a calibrated camera were used to estimate camera poses and the overall trajectory. The pipeline was implemented using different feature matching and tracking approaches for both 2D-2D and 3D-2D pose estimation techniques.

Implementations

Visual Odometry (VO) using 2 approaches for motion estimation
  • 2D-2D - Feature Matching and Feature Tracking
  • 3D-2D - Feature Matching and Feature Tracking
Two other projects were done in addition to Visual Odometry. 
The first one is Structure From Motion(SFM) which is aimed to generate a sparse 3D reconstruction of a scene using random camera images


2D-2D Approach for Motion Estimation

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3D-2D approach for motion estimation

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Reprojection error in 3D-2D approach

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Sparse 3D reconstruction.
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​Structure of Motion (SFM):
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​​.
GitHub

Team

  • Arihanr Gaur
  • Kushagra Srivastava
  • Saurabh Kemekar
  • Bipasha Parui
  • Karthik Raman
  • ​Parees Pathak
  • Sushlok Shah

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  • Our Lab
    • About
    • Research Themes
    • Gallery
    • Exhibitions
    • Workshops >
      • Workshop Info
      • FAQ
    • Intern Diaries
  • Projects
    • Flagship Projects
    • Summer Projects
  • Publications
  • Our Team
    • Professor Incharge
    • Alumni >
      • Batch 2014
      • Batch 2016
      • Batch 2017
      • Batch 2018
      • Batch 2019
      • Batch 2020
      • Batch 2021
      • Batch 2022
    • Core Coordinators
    • Junior Year Coordinators
  • Contact
  • Spin-offs
    • Makxenia
    • AidBots
  • Intranet