Michael Gallant

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In this tutorial paper, we discuss the ITU-T H.263+ (or H.263 Version 2) low-bit-rate video coding standard. We first describe, briefly, the H.263 standard including its optional modes. We then address the 12 new negotiable modes of H.263+. Next, we present experimental results for these modes, based on our public-domain implementation (see our Web site at(More)
In this paper, we present an effective framework for increasing the error-resilience of low bit-rate video communications over error-prone packet-switched networks. Our framework is based on the principle of layered coding with transport prioritization. We introduce a rate-distortion optimized mode-selection algorithm for our prioritized layered framework.(More)
We address the problem of robust transmission of compressed visual information over unreliable networks. Our approach employs the principle of multiple-descriptions, through preand post-processing of the image data, without modification to the source or channel codecs. We employ oversampling to add redundancy to the original image data followed by a(More)
We present an efficient computation constrained block-based motion vector estimation algorithm for low bit rate video coding that yields good tradeoffs between motion estimation distortion and number of computations. A reliable predictor determines the search origin, localizing the search process. An efficient search pattern exploits structural constraints(More)
The ITU-T H.263+ low bit-rate video coding standard is Version 2 of the draft international standard ITU-T H.263. Currently, we are a contributing party in the H.263+ standardization effort. In this paper, we discuss this emerging video coding standard and present compression performance results based on our public domain implementation of H.263+.
We have created a new mobile video database that models distortions caused by network impairments. In particular, we simulate stalling events and startup delays in over-the-top (OTT) mobile streaming videos. We describe the way we simulated diverse stalling events to create a corpus of distorted videos and the human study we conducted to obtain subjective(More)
The vast majority of today's internet video services are consumed over-the-top (OTT) via reliable streaming (HTTP via TCP), where the primary noticeable delivery-related impairments are startup delay and stalling. In this paper we introduce an objective model called the delivery quality score (DQS) model, to predict user's QoE in the presence of such(More)