13.5 Video Object Data Model

Problems:

(1) Difficulties in Defining Attributes :

A description for a semantically meaningful scene is represented as a tuple:

(starting frame#, ending frame#, other attributes to describe the scene).

Problems:

[a] Depending on the describers' viewpoints, so it may have multiple different sets of attribute definitions.

[b] it is difficult to describe the entire contents of a video disc at one time, the incrementally added descriptions will result in a difficulty in defining all attributes in advance.

[c] Conventional ODBMS only provide a mechanism for the inheritance of attribute structures and methods among classes.

(2) Difficulties in Querying :

In conventional database systems, user must know the attribute structures or class structures in order to retrieve desired objects. Not inconvenient.

A mechanism is necessary to decrease the required number of descriptions of attribute definitions for objects.

(3) Treatment of Composed Objects :

Most conventional ODBMSs do not have sufficient facility to generate new classes dynamically.

Basic Ideas
the feathers of this video object Model:

(1) Schema-less Description of Database

(2) Interval Inclusion Inheritance

(3) Composition of Video-Objects Based on is-a Hierarchy.

Arbitrary attributes can be attached to each video object whenever they are necessary.

Ex: A video scene concerned with JOHN and the user want to use his name as the attribute value. If the name attribute does not exist in the database, can add it to this video object at any time.

The notion of inheritance based on the interval inclusion relationship.

Ex: Consider a night scene as a video-object A and another object B is defined over some portion of object A. The object B is also a night scene. (Has the same attribute and value.)

Video Objects

it consists of
(1) its object identifier ( oid for short)
(2) an interval,
(3) and a collection of attribute/value pairs.

Each video-object has a unique object identifier. An interval is presented by the pair of starting frame# and ending frame# .

Generalization Hierarchy for Values and Objects:

a1 a2 means that a1 is-a a2 and that the atomic value a1 is more informative than the atomic value a2.

Example: Figure 13-2

Least Upper Bound of Values:

v1= [ Prime_Minister: Kakuei Tanaka, Location: Tokyo, Action: relaxation],

v2 = [ Year: 1974, Location: Tokyo, Action: Walk],

V1 V2 =[ Location: Tokyo, Action: Walk],

(represents the maximum information.)

Greatest Lower Bound of Values:

V1 = [ Location: Tokyo, Year: 1972, Subjects : { national land development, financial problem}],

v2 = [ Year: 1972, Subjects : { financial problem, social welfare}],

v1^v2 = [ Location: Tokyo, Year: 1972, subjects: {national land development, financial problem, social welfare}],

(represents the minimum information.)

ex: Figure 13-3

Inheritance Based on Interval Inclusion Relationship

Inheritable Attributes	Event_type, Location, President, Prime_Minister, Thematic_Person, Year
Non-Inheritable Attributes	Action, Private_life, Subjects

Table 13-1 Inheritable attributes in the example video database.

Composition Operations for Video-Objects

Merging Video-objects:

example: figure 13-4

Overlapping video-objects:

example: figure 13-5

13.5 Video Object Data Model

(1) Difficulties in Defining Attributes :

A description for a semantically meaningful scene is represented as a tuple:

(starting frame#, ending frame#, other attributes to describe the scene).

Problems:

[a] Depending on the describers' viewpoints, so it may have multiple different sets of attribute definitions.

[b] it is difficult to describe the entire contents of a video disc at one time, the incrementally added descriptions will result in a difficulty in defining all attributes in advance.

[c] Conventional ODBMS only provide a mechanism for the inheritance of attribute structures and methods among classes.

(2) Difficulties in Querying :

In conventional database systems, user must know the attribute structures or class structures in order to retrieve desired objects. Not inconvenient.

A mechanism is necessary to decrease the required number of descriptions of attribute definitions for objects.

(3) Treatment of Composed Objects :

Most conventional ODBMSs do not have sufficient facility to generate new classes dynamically.

Arbitrary attributes can be attached to each video object whenever they are necessary.

Ex: A video scene concerned with JOHN and the user want to use his name as the attribute value. If the name attribute does not exist in the database, can add it to this video object at any time.

The notion of inheritance based on the interval inclusion relationship.

Ex: Consider a night scene as a video-object A and another object B is defined over some portion of object A. The object B is also a night scene. (Has the same attribute and value.)

Video Objects

Generalization Hierarchy for Values and Objects:

a1 a2 means that a1 is-a a2 and that the atomic value a1 is more informative than the atomic value a2.

Example: Figure 13-2

Least Upper Bound of Values:

v1= [ Prime_Minister: Kakuei Tanaka, Location: Tokyo, Action: relaxation],

v2 = [ Year: 1974, Location: Tokyo, Action: Walk],

V1 V2 =[ Location: Tokyo, Action: Walk],

(represents the maximum information.)

Greatest Lower Bound of Values:

V1 = [ Location: Tokyo, Year: 1972, Subjects : { national land development, financial problem}],

v2 = [ Year: 1972, Subjects : { financial problem, social welfare}],

v1^v2 = [ Location: Tokyo, Year: 1972, subjects: {national land development, financial problem, social welfare}],

(represents the minimum information.)

ex: Figure 13-3

Inheritance Based on Interval Inclusion Relationship

Inheritable Attributes

Event_type, Location, President, Prime_Minister, Thematic_Person, Year

Non-Inheritable Attributes

Action, Private_life, Subjects

Table 13-1 Inheritable attributes in the example video database.

Composition Operations for Video-Objects

Merging Video-objects:

example: figure 13-4

Overlapping video-objects:

example: figure 13-5