Achieving multimedia synchronization between live video and live audio streams using QoS controls

Huang, Chung-Ming; Lee, Ruey-Yang

doi:10.1016/s0140-3664(96)01080-8

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…Normally, to obtain an inter-stream synchronization, a master/slave scheme is used, defining one of the streams as the master stream, and considering the others as the slave streams (as in the example described in Section 3 [2][3][4][5]7,[12][13][14]24,26,28,30,31,35,[38][39][40][41]48,[50][51][52]60,62,63,65,[69][70][71][73][74][75][76][78][79][80][81][82][83][84]88,90,93,94,[97][98][99][100]. There are some proposals in which the master and slave roles are exchanged dynamically, allowing master-slave switching [2,<...>…”

Section: (B) Receiver Controlmentioning

confidence: 99%

“…There are some proposals in which the master and slave roles are exchanged dynamically, allowing master-slave switching [2,4,7,[12][13][14]28,30,31,39,40,62,77,98]. This way, when the asynchrony of a slave stream exceeds a threshold value, the receiver can switch the roles, and consider that stream as the new master one, making the needed required adaptations.…”

Section: (B) Receiver Controlmentioning

confidence: 99%

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Multimedia group and inter-stream synchronization techniques: A comparative study

Boronat

Lloret

García

2009

Information Systems

110

111

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Section: (B) Receiver Controlmentioning

confidence: 99%

Section: (B) Receiver Controlmentioning

confidence: 99%

Multimedia group and inter-stream synchronization techniques: A comparative study

Boronat

Lloret

García

2009

Information Systems

110

111

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“…In contrast, conversational systems tend to rely more on protocol-based techniques [2,[37][38][39][40][41]. Well-known examples include MBONE tools such as ivs, vat and rat [40], which are based on the RTF (Real-Time Frotocol) protocol [41].…”

Section: Temporal Synchrony: Basic Mechanicsmentioning

confidence: 99%

Message Digest (MD5) Algorithm and Secure Hash Algorithm (SHA)

Encyclopedia of Multimedia

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Definition:Medical image segmentation refers to the segmentation of known anatomic structures from medical images.Structures of interest include organs or parts thereof, such as cardiac ventricles or kidneys, abnormalities such as tumors and cysts, as well as other structures such as bones, vessels, brain structures etc. The overall objective of such methods is referred to as computer-aided diagnosis; in other words, they are used for assisting doctors in evaluating medical imagery or in recognizing abnormal findings in a medical image.In contrast to generic segmentation methods, methods used for medical image segmentation are often application-specific; as such, they can make use of prior knowledge for the particular objects of interest and other expected or possible structures in the image. This has led to the development of a wide range of segmentation methods addressing specific problems in medical applications. Some methods proposed in the literature are extensions of methods originally proposed for generic image segmentation. In [1], a modification of the watershed transform is proposed for knee cartilage and gray matter/white matter segmentation in magnetic resonance images (MRI). This introduces prior information in the watershed method via the use of a previous probability calculation for the classes present in the image and via the combination of the watershed transform with atlas registration for the automatic generation of markers.Other methods are more application specific; for example in [2], segmentation tools are developed for use in the study of the function of the brain, i.e. for the classification of brain areas as activating, deactivating, or not activating, using functional magnetic resonance imaging (FMRI) data. The method of [2] performs segmentation based on intensity histogram information, augmented with adaptive spatial regularization using Markov random fields. The latter contributes to improved segmentation as compared to non-spatial mixture models, while not requiring the heuristic fine-tuning that is necessary for non-adaptive spatial regularization previously proposed.Another important appHcation of segmentation tools is in the study of the function of the heart. In [3], a contour detection algorithm based on a radial edge-detection filter is MESSAGE DIGEST (MD5) ALGORITHM AND SECURE HASH ALGORITHM (SHA)Definition: Message Digest and Secure Cash are the standard algorithms to provide data security for multimedia authentication.The MD5 algorithm takes as input a message of arbitrary length and produces as output a 128-bit "fingerprint" or "message digest" of the input message [1]. MD5 is currently a standard, Internet Engineering Task Force (IETF) Request for Comments (RFC) 1321. In 160 256 384 512Each SHA algorithm processes a message in two stages: preprocessing and hash computation. Preprocessing involves padding a message, parsing the padded message into 512-or 1024-bit blocks, and setting initialization values to be used in the hash computation. The hash computation generates a ...

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Multimedia Synchronization — Area Overview

Robbins¹

Encyclopedia of Multimedia

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Achieving multimedia synchronization between live video and live audio streams using QoS controls

Cited by 6 publications

References 15 publications

Multimedia group and inter-stream synchronization techniques: A comparative study

Multimedia group and inter-stream synchronization techniques: A comparative study

Message Digest (MD5) Algorithm and Secure Hash Algorithm (SHA)

Multimedia Synchronization — Area Overview

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