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== Scalable ==
=== Using <input> to add
=== Using <input> to add streams ===
Revision as of 19:35, 18 June 2010
- This article is about COLLADA extensions. For:
COLLADA provides flexibility by allowing applications to define extensions to existing COLLADA elements. These extensions take the form of alternative <technique> elements, additive <extra> elements, and scalable <input> elements.
Extension by alternative
COLLADA enables extensibility and multiple representation of many of its elements using one <technique_common> and zero or more alternative <technique> elements:
- The common technique, which is required by the schema, is a strongly typed representation of the element.
- Other techniques are defined by the vendor supplying the alternative representation. Each <technique> has a profile attribute that specifies the platform (product name or similar) to which the representation applies.
Each alternative representation contains values that describe the element for that profile. The representations may have coherency between profiles, although that is not required. For example, if <technique_common> describes an ambient light, an alternative <technique> for that light could validly describe either a different kind of ambient light or something else, such as an area light, for the specified profile.
Using <technique> to choose profiles
Where alternative choices are possible within the schema, the <technique> element models the alternative extensions. A COLLADA processor chooses one, and only one, of the available alternatives, either the <technique_common> or one of the <technique> elements. For example:
<light> <technique_common> <ambient> <color/> </ambient> </technique_common> <technique profile="alternative_1"> <ambient> <color/> </ambient> </technique> <technique profile="alternative_2"> <arealight /> </technique> </list>
Extension by addition
An extensible schema also requires a means for specifying arbitrary information. This extra information can represent additional real data or semantic (meta) data to the application.
COLLADA represents extra information using <technique> elements within an <extra> element. Each <technique> contains arbitrary XML elements and data and is labeled with a profile attribute specifying the environment to which it applies.
Using <extra> to add data
Here is an example of an <extra> element that outlines both structured and unstructured additional content:
<geometry> <extra> <technique profile="Max" xmlns:max="some/max/schema"> <param name="wow" sid="animated" type="string">a validated string parameter from the COLLADA schema.</param> <max:someElement>defined in the Max schema and validated.</max:someElement> <uhoh>something well-formed and legal, but that can’t be validated because there is no schema for it!</uhoh> </technique> </extra> <geometry>
Scalable Data Streams
The COLLADA schema design takes different approaches for low and high frequency data in order to achieve a good balance between information and (self describing) verbosity. Low frequency data is modeled as individual XML elements and attributes, with descriptive names. High frequency data is modeled as streams (homogeneous arrays) of values, often with a terse element name (e.g.
for "primitive"). High frequency data, such at vertex attribute or animation key-frame data, uses a streaming data model where a data sink connects inputs to a data source. The data sources are represented by the <source> element. Examples of data sinks are: <triangles>, <polylist>, <vertex_weights>, etc.; basically anything that uses the <input> element is a data sink. In COLLADA, the <source> element does not have data semantics. It is raw data that can be shared by any number of data sinks (consumers). It is the consumer of that data that binds a semantic to the data for its own usage model.
Using <input> to add Vertex Attribute streams
The COLLADA geometry model represents a geometry as a high level collection of data sources and sinks. The collection is categorized as a mesh, convex mesh, spline, or boundary representation (B-rep). The data sinks are geometric primitives that describe the collation of data from their input streams, one vertex at a time; thereby assembling the primitives.
The number of attributes values per vertex is not predefined or fixed. Each geometric primitive can declare an unbounded number if inputs from which to assemble primitives.