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Presented by, Pradeep Thomas Thundiyil M.Tech 1 st   Sem DCN November 1, 2009
Contents ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],November 1, 2009
Objective ,[object Object],[object Object],November 1, 2009
Cognitive Impairment ? ,[object Object],[object Object],[object Object],[object Object],November 1, 2009
Introduction ,[object Object],[object Object],[object Object],November 1, 2009
November 1, 2009
Concept ,[object Object],[object Object],November 1, 2009
System Overview ,[object Object],[object Object],[object Object],November 1, 2009
Working ,[object Object],[object Object],[object Object],[object Object],[object Object],November 1, 2009 Working Steps
System Diagram ,[object Object],November 1, 2009
Implementation November 1, 2009
Feature Detection ,[object Object],[object Object],[object Object],[object Object],November 1, 2009
[object Object],Mean Shift Method November 1, 2009 A geometrical feature detection system which is to be used for data acquisition and pre-processing, segmentation and landmark extraction and characterisation.  Cornerity  Metric
Segmentation & Corner finding results ,[object Object],[object Object],[object Object],November 1, 2009
Feature Matching ,[object Object],[object Object],[object Object],[object Object],November 1, 2009
RANSAC Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],November 1, 2009
Results of the point-correspondence algorithm in the Computer Science Building. (a) Numbers label the detected points on the image and the corresponding matched points on the floor plan.  (b) The floor plan is warped into the image space and overlaid on the original image. This example has 10 image points and 32 map points and completes matching in about 4 seconds. November 1, 2009
Augmenting Images ,[object Object],[object Object],[object Object],November 1, 2009
Feasibility Analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],November 1, 2009
Changes in floor material, reflective floors and structures like catwalks causes problems.  People or clutter in the hallways causes problems in detecting features.  Environments with low contrast difference between floors and walls. November 1, 2009 Limitations Examples that pose problems for Segmentation.
System Extensions ,[object Object],[object Object],[object Object],November 1, 2009
Conclusion & Future Works ,[object Object],[object Object],[object Object],[object Object],November 1, 2009
References ,[object Object],[object Object],[object Object],[object Object],November 1, 2009
Thank  You..! November 1, 2009

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Positioning And Orientation In Indoor Environments Using Camera 2003

  • 1. Presented by, Pradeep Thomas Thundiyil M.Tech 1 st Sem DCN November 1, 2009
  • 2.
  • 3.
  • 4.
  • 5.
  • 7.
  • 8.
  • 9.
  • 10.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17. Results of the point-correspondence algorithm in the Computer Science Building. (a) Numbers label the detected points on the image and the corresponding matched points on the floor plan. (b) The floor plan is warped into the image space and overlaid on the original image. This example has 10 image points and 32 map points and completes matching in about 4 seconds. November 1, 2009
  • 18.
  • 19.
  • 20. Changes in floor material, reflective floors and structures like catwalks causes problems. People or clutter in the hallways causes problems in detecting features. Environments with low contrast difference between floors and walls. November 1, 2009 Limitations Examples that pose problems for Segmentation.
  • 21.
  • 22.
  • 23.
  • 24. Thank You..! November 1, 2009