Information Technology Reference
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as MIDI, AVI, WAV, RealAudio, DTS, or other audio formats, and samples
cannot be less than 16 bits (mono) and cannot have a higher frequency than
44.1 kHz (stereo). Jang et al. [18] proposed the content-based music retrieval
process named Super MBox. They used the acoustic input data (singing,
humming, or a musical instrument playing), which is directly recorded from
a PC microphone for a duration of eight seconds, at an 8-bit resolution, in
mono and with 11,025 units of sample rate. For their system they used pitch
tracking using two methods: first is an autocorrelation function and second
is through the use of the Average Magnitude Difference Function (AMDF).
Both methods are performed in the time domain and have comparable per-
formance. They have tested Super MBox and verified the proposed optimiza-
tion scheme for HFM (Hierarchical Filtering Method). The system apparently
demonstrates the feasibility of real-time music retrieval with a high success
rate. Another issue arises when new formats of music are released. Thus it is
important to combine or to improve the sound retrieval so that it can be used
for multiple sound formats.
A final issue in multimedia data retrieval is how to retrieve video from
the database. Semantic retrieval is one of the hot topics in video retrieval.
Hamminchi et al. [19] describe how a tree-based system works (semantic
retrieval), their algorithm, and details of the tree embedding problem for
MPEG-7. They propose a new framework of semantic searches to solve user
problems for querying multimedia data based on a tree embedding approxi-
mation algorithm, combining the MPEG-7 standard and an ontology. They
use reasoning and embedding tree mechanisms in a complementary way
to retrieve MPEG-7 data from a database. In their framework, they define
a specific ontology domain and integrate it with the MPEG-7 database dur-
ing the indexing process. Their proposed algorithm is excellent for MPEG-7
query work using the tree-based retrieval technique. However, their seman-
tic retrieval research is based only on MPEG-7 data and has not been applied
directly to other formats.
12.2.3 accessing Multimedia Data through P2P Networks
Many researchers refer to Napster [20], Gnutella [21,22] and JXTASearch [23]
when considering peer-to-peer (P2P) networks. Napster was the original P2P
application that made the P2P idea popular. Peer-to-peer systems offer an
alternative to traditional client-server systems for some application domains.
In P2P systems every node (peer) of the system acts as both client and server
and provides part of the overall information available from the system. The
P2P approach circumvents many of the problems associated with client-
server systems but results in considerably more complex searching, node
organization, security, and so on. P2P networks can be divided into two
classes: structured and unstructured networks [24]. In a structured P2P over-
lay network the topology is tightly controlled and the content is placed not
at random peers but at specified locations that will make subsequent queries
