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Pictorial Query by Example (PQBE) for Image Retrieval: Symbolic Images & Direction Relations

Explore the concept of Symbolic Images and Direction Relations in Pictorial Query-by-example (PQBE) for image database retrieval. Learn about implementing queries using skeleton images, applications, and constructing symbolic images.

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Pictorial Query by Example (PQBE) for Image Retrieval: Symbolic Images & Direction Relations

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  1. Pictorial Query by ExamplePQBE Vida Movahedi Mar. 2007

  2. Contents • Symbolic Images • Direction Relations • PQBE • Implementation of queries using skeleton images • Sample application • Construction of Symbolic Images

  3. Symbolic Image • Symbolic image: is an array representing a set of objects and a set of direction relations among them • Used in • Context-based retrieval in image databases • Spatial reasoning • Path planning • Image similarity retrieval

  4. Direction Relations • Primitive Direction relations: • {NorthWest, RestrictedNorth, NorthEast,RestrictedWest, SamePosition, RestrictedEast, SouthWest, RestrictedSouth, SouthEast} • Y: reference object • Direction relation of primary object • All primitives are transitive, SamePosition is symmetric

  5. Introducing PQBE • Pictorial Query-by-example • Generalizes from example given by user • Uses skeleton images (which are symbolic images) as queries • Ability to express negation, union, intersection, join, etc

  6. Description by Sets • O(I): objects of image I • C(I): primitive direction relations (constraints) between all pairs of objects in image I • Example: • O(u)={O, P, Q} • C(u)={RestrictedEast(Q,O),SouthWest(O,P), RestrictedNorth(P,Q)} • Note SamePosition and converse relations not included for simplicity u

  7. Query Queries with one skeleton image Database Image Constant _: variables (for objects/ images) are precede by ‘_’ P: printing character, when before an object variable/constant causes its value to be retrieved and displayed

  8. Query • A symbolic image I is a subimage of J iff O(I)O(J) & C(I)C(J) • Result of a query: set of all symbolic (sub)images that satisfy the spatial conditions imposed by sets O and C of skeleton images • Assumptions: closed world, domain closure, unique name

  9. Example: Query 1 Retrieve the subimages of s that contain an object X where X is NorthEast of B in s.

  10. Example: Query 2

  11. Example: Query 3 & 4

  12. Example: Queries 5-7

  13. Querying object configurations

  14. Querying relations between objects

  15. Union, Intersection, Join

  16. Queries with multiple images

  17. Queries with image retrieval

  18. Update Operations • P: printing character  Select • R: removing character  Delete • I: inserting character  Insert

  19. Application: Geographical Queries Maps of cities in Central Europe Symbolic Image A sample query

  20. Spatial Representation • preserve location in space • without incorporating information such as shape, size, texture, or color of objects • e.g. subway maps contain no information about the shapes of the stations

  21. Different Areas, Different Goals • Explanatory and predictive power • Computational models of Vision and Imagery • Expressive power and inferential adequacy • Artificial Intelligence representation schemes • Efficient manipulation of large amounts of geographic and geometric data • Spatial Databases

  22. Construction of 2D-G string Segmented Original Image Cutting function: detects and records differences in object projections on the x and y axis

  23. Construction of Symbolic Arrays

  24. References [1] Dimitris Papadias and Timos Sellis (1995), A Pictorial Query-By-Example Language, Journal of Visual Languages and Computing, vol. 6, pp. 53-72. [2] Dimitris Papadias and Timos Sellis (1994), Qualitative Representation of Spatial Knowledge in Two-Dimensional Space, Very Large Databases Journal, Special Issues on Spatial Databases, vol. 3, pp. 476-513.

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