The Querying Interface

Next: Working Canvas Up: VisualMOQL Overview Previous: Introduction

[Please remove <h1>]

VisualMOQL has these particular features:

It is a declarative visual query language with a step by step construction of queries, close to the way people think in natural languages.
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.
It combines several querying approaches: semantic-based (query image semantics using salient objects), attribute-based (specify and compare attribute values), and cognitive-based (query by example). 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

) 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:

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.
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.
A horizontal 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.
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.
A working canvas where the user constructs queries step by step.
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.

Next: Working Canvas Up: VisualMOQL Overview Previous: Introduction

Demo

Vincent Oria
1998-11-24