700 research outputs found
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Error resilient video transcoding for robust inter-network communications using GPRS
A novel fully comprehensive mobile video communications
system is proposed in this paper. This system exploits
the useful rate management features of the video transcoders and
combines them with error resilience for transmissions of coded
video streams over general packet radio service (GPRS) mobileaccess
networks. The error-resilient video transcoding operation
takes place at a centralized point, referred to as a video proxy,
which provides the necessary output transmission rates with the
required amount of robustness. With the use of this proposed
algorithm, error resilience can be added to an already compressed
video stream at an intermediate stage at the edge of two or more
different networks through two resilience schemes, namely the
adaptive intra refresh (AIR) and feedback control signaling (FCS)
methods. Both resilience tools impose an output rate increase
which can also be prevented with the proposed novel technique in
this paper. Thus, an error-resilient video transcoding scheme is
presented to give robust video outputs at near target transmission
rates that only require the same number of GPRS timeslots as
the nonresilient schemes. Moreover, an ultimate robustness is
also accomplished with the combination of the two resilience
algorithms at the video proxy. Extensive computer simulations
demonstrate the effectiveness of the proposed system
Dynamic region of interest transcoding for multipoint video conferencing
This paper presents a region of interest transcoding scheme for multipoint video conferencing to enhance the visual quality. In a multipoint videoconference, usually there are only one or two active conferees at one time which are the regions of interest to the other conferees involved. We propose a Dynamic Sub-Window Skipping (DSWS) scheme to firstly identify the active participants from the multiple incoming encoded video streams by calculating the motion activity of each sub-window, and secondly reduce the frame-rates of the motion inactive participants by skipping these less-important subwindows. The bits saved by the skipping operation are reallocated to the active sub-windows to enhance the regions of interest. We also propose a low-complexity scheme to compose and trace the unavailable motion vectors with a good accuracy in the dropped inactive sub-windows after performing the DSWS. Simulation results show that the proposed methods not only significantly improve the visual quality on the active subwindows without introducing serious visual quality degradation in the inactive ones, but also reduce the computational complexity and avoid whole-frame skipping. Moreover, the proposed algorithm is fully compatible with the H.263 video coding standard. 1
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Scalable and network aware video coding for advanced communications over heterogeneous networks
This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityThis work addresses the issues concerned with the provision of scalable video services over heterogeneous networks particularly with regards to dynamic adaptation and userâs acceptable quality of service.
In order to provide and sustain an adaptive and network friendly multimedia communication service, a suite of techniques that achieved automatic scalability and adaptation are developed. These techniques are evaluated objectively and subjectively to assess the Quality of Service (QoS) provided to diverse users with variable constraints and dynamic resources. The research ensured the consideration of various levels of user acceptable QoS The techniques are further evaluated with view to establish their performance against state of the art scalable and non-scalable techniques.
To further improve the adaptability of the designed techniques, several experiments and real time simulations are conducted with the aim of determining the optimum performance with various coding parameters and scenarios. The coding parameters and scenarios are evaluated and analyzed to determine their performance using various types of video content and formats. Several algorithms are developed to provide a dynamic adaptation of coding tools and parameters to specific video content type, format and bandwidth of transmission.
Due to the nature of heterogeneous networks where channel conditions, terminals, users capabilities and preferences etc are unpredictably changing, hence limiting the adaptability of a specific technique adopted, a Dynamic Scalability Decision Making Algorithm (SADMA) is developed. The algorithm autonomously selects one of the designed scalability techniques basing its decision on the monitored and reported channel conditions. Experiments were conducted using a purpose-built heterogeneous network simulator and the network-aware selection of the scalability techniques is based on real time simulation results. A technique with a minimum delay, low bit-rate, low frame rate and low quality is adopted as a reactive measure to a predicted bad channel condition. If the use of the techniques is not favoured due to deteriorating channel conditions reported, a reduced layered stream or base layer is used. If the network status does not allow the use of the base layer, then the stream uses parameter identifiers with high efficiency to improve the scalability and adaptation of the video service.
To further improve the flexibility and efficiency of the algorithm, a dynamic de-blocking filter and lambda value selection are analyzed and introduced in the algorithm. Various methods, interfaces and algorithms are defined for transcoding from one technique to another and extracting sub-streams when the network conditions do not allow for the transmission of the entire bit-stream
Efficient HEVC-based video adaptation using transcoding
In a video transmission system, it is important to take into account the great diversity of the network/end-user constraints. On the one hand, video content is typically streamed over a network that is characterized by different bandwidth capacities. In many cases, the bandwidth is insufficient to transfer the video at its original quality. On the other hand, a single video is often played by multiple devices like PCs, laptops, and cell phones. Obviously, a single video would not satisfy their different constraints.
These diversities of the network and devices capacity lead to the need for video adaptation techniques, e.g., a reduction of the bit rate or spatial resolution. Video transcoding, which modifies a property of the video without the change of the coding format, has been well-known as an efficient adaptation solution. However, this approach comes along with a high computational complexity, resulting in huge energy consumption in the network and possibly network latency.
This presentation provides several optimization strategies for the transcoding process of HEVC (the latest High Efficiency Video Coding standard) video streams. First, the computational complexity of a bit rate transcoder (transrater) is reduced. We proposed several techniques to speed-up the encoder of a transrater, notably a machine-learning-based approach and a novel coding-mode evaluation strategy have been proposed. Moreover, the motion estimation process of the encoder has been optimized with the use of decision theory and the proposed fast search patterns. Second, the issues and challenges of a spatial transcoder have been solved by using machine-learning algorithms. Thanks to their great performance, the proposed techniques are expected to significantly help HEVC gain popularity in a wide range of modern multimedia applications
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