High Efficiency Video Coding (HEVC) is currently being prepared as the newest video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The main goal ...of the HEVC standardization effort is to enable significantly improved compression performance relative to existing standards-in the range of 50% bit-rate reduction for equal perceptual video quality. This paper provides an overview of the technical features and characteristics of the HEVC standard.
The compression capability of several generations of video coding standards is compared by means of peak signal-to-noise ratio (PSNR) and subjective testing results. A unified approach is applied to ...the analysis of designs, including H.262/MPEG-2 Video, H.263, MPEG-4 Visual, H.264/MPEG-4 Advanced Video Coding (AVC), and High Efficiency Video Coding (HEVC). The results of subjective tests for WVGA and HD sequences indicate that HEVC encoders can achieve equivalent subjective reproduction quality as encoders that conform to H.264/MPEG-4 AVC when using approximately 50% less bit rate on average. The HEVC design is shown to be especially effective for low bit rates, high-resolution video content, and low-delay communication applications. The measured subjective improvement somewhat exceeds the improvement measured by the PSNR metric.
Automatic traffic surveillance usually relies on the estimation of traffic flow parameters through either dedicated sensors or the processing of road surveillance cameras. However, dedicated sensors ...are expensive to deploy and maintain. Moreover, available video processing algorithms usually require a complex multi-step pipeline, unsuited for large scale deployment. Herein, we address the problem of automatically estimating the flow rate (number of vehicles/unit of time) from surveillance cameras at low computation cost. To do so, we rely on end-to-end deep architectures applied to compressed MPEG4 part-2 video streams issued from road surveillance cameras. By leveraging the approximate flow representation induced by the compression, we heavily reduce the computation and memory requirements. We propose three end-to-end deep architectures using this coarse pixel flow representation as input. We also release two datasets, one based on synthetic videos and one collected on industrial tunnel cameras. By training the deep models on the newly introduced datasets, we evidence the effectiveness of predicting the flow rate directly from MPEG4 part-2 compressed video streams. We demonstrate an improved accuracy in comparison with a more classical RGB-based architecture and show an impressive speed up of <inline-formula> <tex-math notation="LaTeX">\times 2065 </tex-math></inline-formula> at prediction time.
We present a new parametrization for point features within monocular simultaneous localization and mapping (SLAM) that permits efficient and accurate representation of uncertainty during undelayed ...initialization and beyond, all within the standard extended Kalman filter (EKF). The key concept is direct parametrization of the inverse depth of features relative to the camera locations from which they were first viewed, which produces measurement equations with a high degree of linearity. Importantly, our parametrization can cope with features over a huge range of depths, even those that are so far from the camera that they present little parallax during motion---maintaining sufficient representative uncertainty that these points retain the opportunity to "come in'' smoothly from infinity if the camera makes larger movements. Feature initialization is undelayed in the sense that even distant features are immediately used to improve camera motion estimates, acting initially as bearing references but not permanently labeled as such. The inverse depth parametrization remains well behaved for features at all stages of SLAM processing, but has the drawback in computational terms that each point is represented by a 6-D state vector as opposed to the standard three of a Euclidean XYZ representation. We show that once the depth estimate of a feature is sufficiently accurate, its representation can safely be converted to the Euclidean XYZ form, and propose a linearity index that allows automatic detection and conversion to maintain maximum efficiency---only low parallax features need be maintained in inverse depth form for long periods. We present a real-time implementation at 30 Hz, where the parametrization is validated in a fully automatic 3-D SLAM system featuring a handheld single camera with no additional sensing. Experiments show robust operation in challenging indoor and outdoor environments with a very large ranges of scene depth, varied motion, and also real time 360 deg loop closing.
In this paper, we address the problem of privacy protection in video surveillance. We introduce two efficient approaches to conceal regions of interest (ROIs) based on transform-domain or ...codestream-domain scrambling. In the first technique, the sign of selected transform coefficients is pseudorandomly flipped during encoding. In the second method, some bits of the codestream are pseudorandomly inverted. We address more specifically the cases of MPEG-4 as it is today the prevailing standard in video surveillance equipment. Simulations show that both techniques successfully hide private data in ROIs while the scene remains comprehensible. Additionally, the amount of noise introduced by the scrambling process can be adjusted. Finally, the impact on coding efficiency performance is small, and the required computational complexity is negligible.
Performance Analysis of SVC Wien, M.; Schwarz, H.; Oelbaum, T.
IEEE transactions on circuits and systems for video technology,
09/2007, Letnik:
17, Številka:
9
Journal Article
Recenzirano
Odprti dostop
This paper provides a performance analysis of the scalable video coding (SVC) extension of H.264/AVC. A short overview presenting the main functionalities of SVC is given and main issues in encoder ...control and bit stream extraction are outlined. Some aspects of rate-distortion optimization in the context of SVC are discussed and strategies for derivation of optimized configurations relative to the investigated scalability scenarios are presented. Based on these methods, rate-distortion results for several SVC configurations are presented and compared to rate-distortion optimized H.264/AVC single layer coding. For reference, a comparison to rate-distortion optimized MPEG-4 visual (advanced simple profile) coding results is provided. The results show that the performance gap between single layer coding and scalable video coding can be very small and that SVC clearly outperforms previous video coding technology such as MPEG-4 ASP.
Embedded systems execute applications with varying performance requirements. These applications exercise the hardware differently depending on the computation task, generating varying workloads with ...time. Energy minimization with such workload and performance variations within (intra) and across (inter) applications is particularly challenging. To address this challenge, we propose an online approach, capable of minimizing energy through adaptation to these variations. At the core of this approach is a reinforcement learning algorithm that suitably selects the appropriate voltage/frequency scaling (VFS) based on workload predictions to meet the applications' performance requirements. The adaptation is then facilitated and expedited through learning transfer, which uses the interaction between the application, runtime, and hardware layers to adjust the VFS. The proposed approach is implemented as a power governor in Linux and extensively validated on an ARM Cortex-A8 running different benchmark applications. We show that with intra- and inter-application variations, our proposed approach can effectively minimize energy consumption by up to 33% compared to the existing approaches. Scaling the approach to multicore systems, we also demonstrate that it can minimize energy by up to 18% with 2× reduction in the learning time when compared with an existing approach.
We evaluate the applicability of a biologically-motivated algorithm to select visually-salient regions of interest in video streams for multiply-foveated video compression. Regions are selected based ...on a nonlinear integration of low-level visual cues, mimicking processing in primate occipital, and posterior parietal cortex. A dynamic foveation filter then blurs every frame, increasingly with distance from salient locations. Sixty-three variants of the algorithm (varying number and shape of virtual foveas, maximum blur, and saliency competition) are evaluated against an outdoor video scene, using MPEG-1 and constant-quality MPEG-4 (DivX) encoding. Additional compression radios of 1.1 to 8.5 are achieved by foveation. Two variants of the algorithm are validated against eye fixations recorded from four to six human observers on a heterogeneous collection of 50 video clips (over 45 000 frames in total). Significantly higher overlap than expected by chance is found between human and algorithmic foveations. With both variants, foveated clips are, on average, approximately half the size of unfoveated clips, for both MPEG-1 and MPEG-4. These results suggest a general-purpose usefulness of the algorithm in improving compression ratios of unconstrained video.
Advances in Scalable Video Coding Ohm, J.-R.
Proceedings of the IEEE,
2005-Jan., 2005-01-00, 20050101, Letnik:
93, Številka:
1
Journal Article
Recenzirano
Scalable video coding is attractive due to the capability of reconstructing lower resolution or lower quality signals from partial bit streams. This allows for simple solutions in adaptation to ...network and terminal capabilities. Different modalities of scalability are specified by video coding standards like MPEG-2 and MPEG-4. This paper gives a short overview over these techniques and analyzes in more detail the encoder/decoder drift problem, which is the major reason why scalable coding has been significantly less efficient than single-layer coding in most of these implementations. Only recently, new scalable video coding technology has evolved, which seems to close the gap of compression performance compared to state of the art single-layer video coding. New methods of efficient enhancement layer prediction were developed to improve traditional (motion-compensated hybrid) scalable coders, providing more flexible compromises on the drift problem. As a new technology trend, motion-compensated spatiotemporal wavelet coding has matured which entirely discards the drift and allows most flexible combinations of spatial, temporal, and signal-to-noise ratio (SNR) scalability with fine granularity over a broad range of data rates.
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