A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks

Adaptive network abstraction layer packetization for low bit rate H.264/AVC video transmission over wireless mobile networks under cross layer optimization

Master'sMASTER OF ENGINEERIN

Design and evaluation of novel scalability techniques for adaptation over heterogeneous networks

This paper addresses the issues concerned with the provision of scalable video services over heterogeneous networks particularly with regards to dynamic adaptation and user’s 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 using H.264/AVC Extension codec platform. The objective, subjective and real time performances of the techniques are evaluated to assess the Quality of Service (QoS) provided to diverse users with variable constraints and dynamic resources. The techniques are further evaluated with view to establish their performance against state of the art scalable and none-scalable techniques. Several experiments and simulations revealed that the proposed techniques outperformed state-of- the-art and none-scalable(SL) techniques. The designed techniques provide an automated scalability adaptation on the video stream and showed up to 50% gain in scalability adaptation against single layer (SL) and none-combined scalability techniques

A neighbourhood analysis based technique for real-time error concealment in H.264 intra pictures

H.264s extensive use of context-based adaptive binary arithmetic or variable length coding makes streams highly susceptible to channel errors, a common occurrence over networks such as those used by mobile devices. Even a single bit error will cause a decoder to discard all stream data up to the next fixed length resynchronisation point, the worst scenario is that an entire slice is lost. In cases where retransmission and forward error concealment are not possible, a decoder should conceal any erroneous data in order to minimise the impact on the viewer. Stream errors can often be spotted early in the decode cycle of a macroblock which if aborted can provide unused processor cycles, these can instead be used to conceal errors at minimal cost, even as part of a real time system. This paper demonstrates a technique that utilises Sobel convolution kernels to quickly analyse the neighbourhood surrounding erroneous macroblocks before performing a weighted multi-directional interpolation. This generates significantly improved statistical (PSNR) and visual (IEEE structural similarity) results when compared to the commonly used weighted pixel value averaging. Furthermore it is also computationally scalable, both during analysis and concealment, achieving maximum performance from the spare processing power available

Distributed Coding/Decoding Complexity in Video Sensor Networks

Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality

Temporal video transcoding from H.264/AVC-to-SVC for digital TV broadcasting

Mobile digital TV environments demand flexible video compression like scalable video coding (SVC) because of varying bandwidths and devices. Since existing infrastructures highly rely on H.264/AVC video compression, network providers could adapt the current H.264/AVC encoded video to SVC. This adaptation needs to be done efficiently to reduce processing power and operational cost. This paper proposes two techniques to convert an H.264/AVC bitstream in Baseline (P-pictures based) and Main Profile (B-pictures based) without scalability to a scalable bitstream with temporal scalability as part of a framework for low-complexity video adaptation for digital TV broadcasting. Our approaches are based on accelerating the interprediction, focusing on reducing the coding complexity of mode decision and motion estimation tasks of the encoder stage by using information available after the H. 264/AVC decoding stage. The results show that when our techniques are applied, the complexity is reduced by 98 % while maintaining coding efficiency