H.264/AVC, the result of the collaboration between the ISO/IEC Moving Picture Experts Group and the ITU-T Video Coding Experts Group, is the latest standard for video coding. The goals of this standardization effort were enhanced compression efficiency, network friendly video representation for interactive (video telephony) and non-interactive applications (broadcast, streaming, storage, video on demand). H.264/AVC provides gains in compression efficiency of up to 50% over a wide range of bit rates and video resolutions compared to previous standards. Compared to previous standards, the decoder complexity is about four times that of MPEG-2 and two times that of MPEG-4 Visual Simple Profile. This paper provides an overview of the new tools, features and complexity of H.264/AVC.

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Video coding with H.264/AVC: tools, performance, and complexity

Advances in video compression technology have been driven by ever-increasing processing power available in software and hardware. The emerging High Efficiency Video Coding (HEVC) standard aims to provide a doubling in coding efficiency with respect to the H.264/AVC high profile, delivering the same video quality at half the bit rate. In this paper, complexity-related aspects that were considered in the standardization process are described. Furthermore, profiling of reference software and optimized software gives an indication of where HEVC may be more complex than its predecessors and where it may be simpler. Overall, the complexity of HEVC decoders does not appear to be significantly different from that of H.264/AVC decoders; this makes HEVC decoding in software very practical on current hardware. HEVC encoders are expected to be several times more complex than H.264/AVC encoders and will be a subject of research in years to come.

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HEVC Complexity and Implementation Analysis

Video transmission in wireless environments is a challenging task calling for high-compression efficiency as well as a network friendly design. Both have been major goals of the H.264/AVC standardization effort addressing "conversational" (i.e., video telephony) and "nonconversational" (i.e., storage, broadcast, or streaming) applications. The video compression performance of the H.264/AVC video coding layer typically provides a significant improvement. The network-friendly design goal of H.264/AVC is addressed via the network abstraction layer that has been developed to transport the coded video data over any existing and future networks including wireless systems. The main objective of this paper is to provide an overview over the tools which are likely to be used in wireless environments and discusses the most challenging application, wireless conversational services in greater detail. Appropriate justifications for the application of different tools based on experimental results are presented.

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H.264/AVC in wireless environments

A scalable extension to the H.264/AVC video coding standard has been developed within the joint video team (JVT), a joint organization of the ITU-T video coding group (VCEG) and the ISO/IEC moving picture experts group (MPEG). The extension allows multiple resolutions of an image sequence to be contained in a single bit stream. In this paper, we introduce the spatially scalable extension within the resulting scalable video coding standard. The high-level design is described and individual coding tools are explained. Additionally, encoder issues are identified. Finally, the performance of the design is reported.

Spatial Scalability Within the H.264/AVC Scalable Video Coding Extension

We are experiencing an explosive growth in the number of consumer devices, including smartphones, tablets, web-based computers such as Chromebooks, and wearable devices. For this class of devices, energy efficiency is a first-class concern due to the limited battery capacity and thermal power budget. We find that data movement is a major contributor to the total system energy and execution time in consumer devices. The energy and performance costs of moving data between the memory system and the compute units are significantly higher than the costs of computation. As a result, addressing data movement is crucial for consumer devices. In this work, we comprehensively analyze the energy and performance impact of data movement for several widely-used Google consumer workloads: (1) the Chrome web browser; (2) TensorFlow Mobile, Google's machine learning framework; (3) video playback, and (4) video capture, both of which are used in many video services such as YouTube and Google Hangouts. We find that processing-in-memory (PIM) can significantly reduce data movement for all of these workloads, by performing part of the computation close to memory. Each workload contains simple primitives and functions that contribute to a significant amount of the overall data movement. We investigate whether these primitives and functions are feasible to implement using PIM, given the limited area and power constraints of consumer devices. Our analysis shows that offloading these primitives to PIM logic, consisting of either simple cores or specialized accelerators, eliminates a large amount of data movement, and significantly reduces total system energy (by an average of 55.4% across the workloads) and execution time (by an average of 54.2%).

Google Workloads for Consumer Devices: Mitigating Data Movement Bottlenecks

We study and analyze the computational complexity of a software-based H.264/AVC (advanced video codec) baseline profile decoder. Our analysis is based on determining the number of basic computational operations required by a decoder to perform the key decoding subfunctions. The frequency of use of each of the required decoding subfunctions is empirically derived using bitstreams generated from two different encoders for a variety of content, resolutions and bit rates. Using the measured frequencies, estimates of the decoder time complexity for various hardware platforms can be determined. A detailed example is provided to assist in deriving time complexity estimates. We compare the resulting estimates to numbers measured for an optimized decoder on the Pentium 3 hardware platform. We then use those numbers to evaluate the dependence of the time complexity of each of the major decoder subfunctions on encoder characteristics, content, resolution and bit rate. Finally, we compare an H.264/AVC-compliant baseline decoder to a decoder that is compliant with the H.263 standard, which is currently dominant in interactive video applications. Both "C" only decoder implementations were compared on a Pentium 3 hardware platform. Our results indicate that an H.264/AVC baseline decoder is approximately 2.5 times more time complex than an H.263 baseline decoder.

M. Horowitz

Papers

H.264/AVC baseline profile decoder complexity analysis