The VisuallVlCQL user manual *
Contents
1. This research is supported by a strategic grant from the Natural Science and Engineering Research Council NSERC of Canada e It combines several querying approaches semantic based query image semantics using salient ob jects attribute based specify and compare attribute values and cognitive based query by exam ple A user can start a query using the semantic and or attribute based approach and then choose an image for a cognitive based query The VisualMOQL window Figure 4 consists of a number of components to design a query The user specifies a query by choosing the image class he wants to query and the salient objects he wants to see in the images Several levels of refinement are offered depending on the type of query and also on the level of precision the user wants the result of the query to have The startup window consists of the following components e A chooser to select the image classes Images stored in the database are categorized into user defined classes By doing this the system allows the user to select a subset of the database to search over The root image class is set as the default e A salient object class browser which allows the user to choose the objects that he wants All salient objects and their associated attribute values are identified during database population These objects are organized into a salient object hierarchy and the root salient object class is set as the default e A hor2. Figure 4 Example of Query The VisualMOQL expression is translated into MOQL Figure 5 before being submitted to the query processor Part of the query result can be seen in Figure 6 FI Query Translation rir Figure 5 Query Translation Netscape Search Result Figure 6 Query Results 4 Conclusion Visual query languages are seen as the next step in query language evolution The aim of visual query languages is to provide users with a friendly interface that easily allows them to pose complex queries Most of the existing visual query languages have a low expressive power due to the fact that they are often just GUIs designed for naive users A powerful query language significantly helps to simplify mul timedia database access Such languages must provide constructs for querying based on the structure of multimedia data For this purpose we have defined MOQL Multimedia Object Query Language MOQL extends OQL by including extensions related to spatial properties temporal properties and presentation properties References CBBt97 R G G Cattell D Barry D Bartels M Berler J Eastman S Gamerman D Jordan A Springer H Strickland and D Wade editors The Object Database Standard ODMG 2 0 Morgan Kaufmann San Francisco CA 1997 LOSO97 J Z Li M T zsu D Szafron and V Oria MOQL A multimedia object query language In Proceedings of the 3rd International Workshop on Multimedia Informat
3. The VisualMOQL user manual DISIMA Group Department of Computing Science University of Alberta Edmonton Alberta Canada T6G 2H1 database cs ualberta ca 1 Introduction VisualMOQL is based on a textual query language that we developed called Multimedia OQL MOQL LOSO97 MOQL extends the standard object query language OQL CBBT97 by adding spatial temporal and presentation properties for content based image and video data retrieval as well as for queries on structured documents Hence MOQL is a general purpose multimedia query languages VisualMOQL implements only the image part of MOQL for the DISIMA project OOLT 97 and combines semantic based query image semantics using salient objects attribute based specify and compare attribute values and cognitive based query by example querying This combination leads to a flexible and yet powerful visual query interface A query specified using VisualMOQL is translated into MOQL to make use of the MOQL parser and query processor 2 The Querying Interface VisualMOQL has these particular features e It is a declarative visual query language with a step by step construction of queries close to the way people think in natural languages e It has a clearly defined semantics based on object calculus This feature can be used to conduct a theoretical study of the language involving concepts such as expressive power and complexity which we consider out of the scope of this paper
4. eck the query canvas to make sure there are no dangling queries That is all the sub queries have to be linked using the AND OR or NOT operators After this it will translate the VisualLMOQL query into MOQL and display the resulting string before submitting it to the query processor 3 An Example of a VisualIMOQL Query Let us express the query Q find images with 2 people next to each other without any building or images with buildings without people or images with animals in VisualMOQL This query is in fact a combination of three queries Qa images with 2 people next to each other without any building e Q images with buildings without people e Q images with animals The final expression of the query is given in Figure 4 Qa is expressed in MOQL by Query AND NOT Query2 where Query is a sub query expressing images with two people one to the west of the other see the working canvas of Figure 4 and Query2 expresses images with buildings Qs is expressed in MOQL by Query3 AND NOT Query4 where Query expresses images with buildings and Query4 expresses images with people Qe is expressed by the sub query Queryd and expresses images with animals The final expression is obtained by combining the sub queries using the OR connective Netscape pe Slop http www cs ualberta ca edatabase DISIMA Interface html Fi J Work Canvas Revise Query ean ie ona i Query Canvas o 0 0 0 o oo o o ooon
5. ion Systems pages 19 28 Como Italy September 1997 OOLt97 V Oria M T zsu X Li L Liu J Li Y Niu and P J Iglinski Modeling images for content based queries The DISIMA approach In Proceedings of 2nd International Conference of Visual Information Systems pages 339 346 San Diego California December 1997
6. izontal slider to specify the maximum number of images that will be returned as the result of the query This is a quality of service parameter used by the query result presentation interface e A horizontal slider to specify the similarity threshold between the query image and the target images stored in the database It is also used for color comparison This is also a quality of service parameter for the presentation interface e A working canvas where the user constructs queries step by step e A query canvas where the user can construct compound queries based on simple queries sub queries defined in the working canvas using AND OR and NOT operators 2 1 Working Canvas The working canvas is where the user constructs or modifies query blocks The user first selects an image class and then selects a salient object class in the class browser The user inserts the selected salient object in the canvas by pressing the Insert button The object appears as a rectangle in the working canvas This rectangle is also used for determining the spatial relationships between objects It could later be resized and moved The user can also define the color shape texture and other attribute values of any objects on canvas by using a dialog box shown in Figure 1 VisualMOQL allows the user to compare textual attributes The default comparison predicate is but can be changed to lt gt lt gt lt gt Since the va
7. og box for defining image properties x axis and or y axis matter The centroid of the rectangles representing salient objects are used to cal culate the directional relationships When both axes matter we can express complex spatial relationships such as northwest southeast overlap etc When the user specifies that only one axis matters the spatial relationships are north south east or west We will use the term sub query to refer to query blocks obtained from the working canvas By clicking on the Validate button the user ends the sub query specification The sub query is then moved into the query canvas where it can be combined with other sub queries to form the final query 2 2 Query Canvas The query canvas is the space for the user to construct compound queries Each sub query is represented by a square box on the query canvas and named Query n n is an integer Compound queries are constructed by combining sub queries or smaller compound queries using AND OR and NOT operators A sub query in the query canvas can be modified and revalidated at any stage by using the Edit button This moves the sub query to the working canvas Finally the user presses the query button to submit the query Before translating the visual query Define Relation Please define the relationship between object 5101 and 0102 Figure 3 Dialog box for defining directional relationship constructed by the user the system will ch
8. riable used to refer to objects in the MOQL translation are shown on the object icons they can be used to express join operators For example find images with 2 persons of the same name can be expressed by inserting two salient objects of type person in the working canvas Assume VisualMOQL refers respectively to them as P01 and P02 Then the user can edit one of the salient objects let us say P01 and type P02 name as the value for the attribute name Figure 1 The query can involve image global properties like name of the photographer or the time the image was taken A dialog box Figure 2 obtained by clicking on the button Image Property is provided to let the user enter such information Edit Object Please define the attributes of object Person P102 Color Similarity Shape Similarity N 5 oO Circle Oval Rectangle Square Polygon Polyline Segment Add Delete Clear Colors Delete Clear Move Resize Done Cancel Java Applet Window Figure 1 Dialog box for editing object attributes Topological relationships will be added automatically for any intersected objects Directional relation ships have to be defined explicitly through a dialog box shown in Figure 3 The user specifies which axes Define Image Property Select Image Class Color Similarity N Add Delete Clear Colors none 7 Done Cancel Java Applet Window Figure 2 Dial
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