Depth image recognition using isomorphic graph theory

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registration of depth-images to each other using graph isomorphism

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Depth image recognition using isomorphic graph theory

  1. 1. Depth image recognition using isomorphic graph theory 1
  2. 2. Our project... ● ● ● ● We try to construct a mesh of the world using the data from a depth sensing camera. Having the depth images Transforming to normal images Apply billboard concept ( each region / plane in different color) 2
  3. 3. Image == sub-graph? ● ● Lets assume that we can perfectly recognize objects in an image The image graph is a sub-graph of the real world 3
  4. 4. Image analysis RGB Images Normal Maps Region Growing Images 4
  5. 5. Graph-based object recognition ● ● Objects can be matched using region growing Each object in image → Node ● ● ● RGB histogram is the “color” of the node Average color pixel of each Node(region) Edges are assigned to neighbouring regions 5
  6. 6. Graph-based object recognition (2) ● ● ● In image sequences, nodes represent objects. The nodes of the graph can be used for pose estimation Saved they can be used for global positioning 6
  7. 7. One approach ● ● ● ● ● Recursive color mapping to detect each region One random pixel is given, a contour is obtained by color flooding and a new node is created The process is repeated for every border pixel An edge is created when two regions are neighbors 7
  8. 8. The sequence Nodes Delaunay Voronoi 8
  9. 9. Finding the isomorphisms 9
  10. 10. Finding the isomorphisms 10
  11. 11. In the end ● ● When the largest isomorphic sub-graph is found we can see if the images have matched. Then its just looking at the sizes.. ? 11
  12. 12. Demo-time 12

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