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SSM is a technology developed at HP Laboratories for representation and
end-to-end adaptation of arbitrary scalable content in a fully format and media
non-specific manner. Scalable bit-streams are naturally organized in a symmetric
multi-dimensional logical structure, and any adaptation is essentially a
downward manipulation of this model. Higher logical constructs are defined on
top of this multi-tier structure to make the model more generally applicable to
a variety of bit-streams involving rich media. The resultant composite model is
referred to as the Structured Scalable Meta-format (SSM). Apart from the implicit
bit-stream constraints that must be satisfied to make a scalable bit-stream
SSM-compliant, two other elements that need to be standardized to build a complete
adaptation and delivery infrastructure based on SSM are: (1) a binary or XML
description of the structure of the bit-stream resource and how it is to be
manipulated to obtain various adapted versions; and (2) an XML specification of
outbound constraints derived from capabilities and preferences of receiving terminals.
By interpreting the descriptor and the constraints a universal adaptation engine can
adapt the content appropriately to suit the specified needs and preferences of recipients,
without knowledge of the specifics of the content, its encoding and/or encryption.
With universal adaptation engines, different adaptation infrastructures are no longer
needed for different types of scalable media.
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The bottom-line is: if some types of compressed content (video, images, audio, etc.),
plus metadata, are encapsulated in the proposed metaformat, then it is possible to
do many types of processing in the compressed data (scaling, change of quality, etc.),
even if the machine doing the processing does not know what type of media it is or the
type of compression used (corollary: even if the data is encrypted). While this
may be surprising to some, and straightforward to others, the practical problem is how to
do it efficiently, and SSM is the solution we propose.
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