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The increasing popularity of Ambisonics as a spatial audio format for streaming services poses new challenges to existing audio coding techniques. Immersive audio delivered to mobile devices requires an efficient bitrate compression that does not affect the spatial quality of the content. Good localizability of virtual sound sources is one of the key elements that must be preserved. This study was conducted to investigate the localization precision of virtual sound source presentations within Ambisonic scenes encoded with Opus low-bitrate compression at different bitrates and Ambisonic orders (1st, 3rd, and 5th). The test stimuli were reproduced over a 50-channel spherical loudspeaker configuration and binaurally using individually measured and generic Head-Related Transfer Functions (HRTFs). Participants were asked to adjust the position of a virtual acoustic pointer to match the position of virtual sound source within the bitrate-compressed Ambisonic scene. Results show that auditory localization in low-bitrate compressed Ambisonic scenes is not significantly affected by codec parameters. The key factors influencing localization are the rendering method and Ambisonic order truncation. This suggests that efficient perceptual coding might be successfully used for mobile spatial audio delivery.
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van Schalkwyk, J. J. D. "Low bitrate video coding with depth compensation." IEE Proceedings - Vision, Image, and Signal Processing 141, no. 3 (1994): 149. http://dx.doi.org/10.1049/ip-vis:19941056.
Wu, Dapeng, Linfeng Cui, Tong Tang, and Ruyan Wang. "Adaptive Bandwidth Prediction and Smoothing Glitches in Low-Latency Live Streaming." Security and Communication Networks 2022 (May 9, 2022): 1–13. http://dx.doi.org/10.1155/2022/4992957.
HTTP adaptive streaming (HAS) technologies such as dynamic adaptive streaming over HTTP (DASH) and common media application format (CMAF) are now used extensively to deliver live streaming services to large numbers of viewers. However, in dynamic networks, inaccurate bandwidth prediction may result in the wrong request of bitrate, and short-term network fluctuations may produce glitches, causing unnecessary bitrate switching, thereby degrading clients' Quality of Experience (QoE). To tackle this, we propose adaptive bandwidth prediction and smoothing glitches in low-latency live streaming (called APSG) in this article. Concretely, firstly, the size of random bandwidth fluctuations is exploited as the weight of exponentially weighted moving average (EWMA) for adaptive bandwidth prediction; in addition to bandwidth prediction and buffer occupancy, glitches phenomena under a stable network environment are taken into account to enhance the viewing experience of clients. Finally, experimental results show that compared to traditional ABR algorithms under a stable network environment, APSG could reduce the number of bitrate switches and latency by up to 72.6% and 27.3%, respectively; under a dynamic network environment, APSG could reduce the number of bitrate switches and latency by up to 53.8% and 23.6%, respectively.
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Kim, Hyung Yong, Ji Won Yoon, Won Ik Cho, and Nam Soo Kim. "Neurally Optimized Decoder for Low Bitrate Speech Codec." IEEE Signal Processing Letters 29 (2022): 244–48. http://dx.doi.org/10.1109/lsp.2021.3132557.
Georgis, Georgios, George Lentaris, and Dionysios Reisis. "Reduced Complexity Superresolution for Low-Bitrate Video Compression." IEEE Transactions on Circuits and Systems for Video Technology 26, no. 2 (February 2016): 332–45. http://dx.doi.org/10.1109/tcsvt.2015.2389431.
Chandrasekhar, Vijay, Gabriel Takacs, David M. Chen, Sam S. Tsai, Yuriy Reznik, Radek Grzeszczuk, and Bernd Girod. "Compressed Histogram of Gradients: A Low-Bitrate Descriptor." International Journal of Computer Vision 96, no. 3 (May 15, 2011): 384–99. http://dx.doi.org/10.1007/s11263-011-0453-z.
Ebrahimi, T., E. Reusens, and Wei Li. "New trends in very low bitrate video coding." Proceedings of the IEEE 83, no. 6 (June 1995): 877–91. http://dx.doi.org/10.1109/5.387090.
Traditional DASH (dynamic adaptation streaming over HTTP(i.e., HyperText Transfer Protocol)) bitrate strategy cannot differentiate segments with different complexities of video content, resulting in the user’s QoE (quality of experience) of segments with high content complexity as worse than that with low content complexity. In case of this, this paper firstly studies video coding and puts forward the definition of video content complexity. Then the effects of content complexity on user’s QoE is analyzed and the QoE utility function of the segment is formulated based on its MOS (mean opinion score, related to the content complexity and bitrate) and bitrate switching between consecutive segments. Last, in order to maximize user’s QoE, this paper proposes VCC-DASH (video content complexity-aware DASH bitrate adaptation strategy) under the constraints of the network bandwidth and the buffer occupancy. In simulations, we compare VCC-DASH with the classical bitrate adaptation strategy proposed by Liu et al. (LIU’s strategy, for short). The simulation results show that the two strategies have similar performances in bitrate switching numbers, playback interruption times, and buffer lengths. In addition, it is more important for simulation results to reveal that VCC-DASH’s average bitrate is much higher than that of LIU’s strategy, which means that VCC-DASH can make fuller use of the network bandwidth than LIU’s strategy does. Moreover, the MOS distribution of the VCC-DASH is more concentrated on the better scores “4~5”, which profit from its content complexity-aware adaptation to allocate more bandwidth resources to high-complexity segments.
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Liang, Xiaoyun, Zhaohong Li, Zhonghao Li, and Zhenzhen Zhang. "Fake Bitrate Detection of HEVC Videos Based on Prediction Process." Symmetry 11, no. 7 (July 15, 2019): 918. http://dx.doi.org/10.3390/sym11070918.
In order to defraud click-through rate, some merchants recompress the low-bitrate video to a high-bitrate one without improving the video quality. This behavior deceives viewers and wastes network resources. Therefore, a stable algorithm that detects fake bitrate videos is urgently needed. High-Efficiency Video Coding (HEVC) is a worldwide popular video coding standard. Hence, in this paper, a robust algorithm is proposed to detect HEVC fake bitrate videos. Firstly, five effective feature sets are extracted from the prediction process of HEVC, including Coding Unit of I-picture/P-picture partitioning modes, Prediction Unit of I-picture/P-picture partitioning modes, Intra Prediction Modes of I-picture. Secondly, feature concatenation is adopted to enhance the expressiveness and improve the effectiveness of the features. Finally, five single feature sets and three concatenate feature sets are separately sent to the support vector machine for modeling and testing. The performance of the proposed algorithm is compared with state-of-the-art algorithms on HEVC videos of various resolutions and fake bitrates. The results show that the proposed algorithm can not only can better detect HEVC fake bitrate videos, but also has strong robustness against frame deletion, copy-paste, and shifted Group of Picture structure attacks.
Davison, Brian C. (Brian Candler). "Image enhancements for low-bitrate videocoding." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/41374.
Lopes, Fernando Jose Pimentel. "Motion estimation for very low bitrate video coding." Thesis, University of Essex, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.395877.
Nilsson, Jonas, and Jesper Nilsson. "Low Bitrate Video and Audio Codecs for Internet Communication." Thesis, Blekinge Tekniska Högskola, Institutionen för telekommunikation och signalbehandling, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3969.
This master thesis discusses the design and the implementation of an own developed wavelet-based codec for both video and image compression. The codec is specifically designed for low bitrate video with minimum complexity for use in online gaming environments. Results indicate that the performance of the codec in many areas equals or even surpasses that of the international JPEG 2000 standard. We believe that it is suitable for any situation where low bitrate is desirable, e.g. video conferences and mobile communications. The game development company Moosehill Productions AB has shown great interest in our codec and its possible applications. We have also implemented an existing audio solution for low bandwidth use. Wavelet-baserad bild/video kompression. Jonas Nilsson, Jesper Nilsson Lovägen 13, 37250 Kallinge tel: 0709708617
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Söderström, Ulrik. "Very Low Bitrate Video Communication : A Principal Component Analysis Approach." Doctoral thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1808.
A large amount of the information in conversations come from non-verbal cues such as facial expressions and body gesture. These cues are lost when we don't communicate face-to-face. But face-to-face communication doesn't have to happen in person. With video communication we can at least deliver information about the facial mimic and some gestures. This thesis is about video communication over distances; communication that can be available over networks with low capacity since the bitrate needed for video communication is low. A visual image needs to have high quality and resolution to be semantically meaningful for communication. To deliver such video over networks require that the video is compressed. The standard way to compress video images, used by H.264 and MPEG-4, is to divide the image into blocks and represent each block with mathematical waveforms; usually frequency features. These mathematical waveforms are quite good at representing any kind of video since they do not resemble anything; they are just frequency features. But since they are completely arbitrary they cannot compress video enough to enable use over networks with limited capacity, such as GSM and GPRS. Another issue is that such codecs have a high complexity because of the redundancy removal with positional shift of the blocks. High complexity and bitrate means that a device has to consume a large amount of energy for encoding, decoding and transmission of such video; with energy being a very important factor for battery-driven devices. Drawbacks of standard video coding mean that it isn't possible to deliver video anywhere and anytime when it is compressed with such codecs. To resolve these issues we have developed a totally new type of video coding. Instead of using mathematical waveforms for representation we use faces to represent faces. This makes the compression much more efficient than if waveforms are used even though the faces are person-dependent. By building a model of the changes in the face, the facial mimic, this model can be used to encode the images. The model consists of representative facial images and we use a powerful mathematical tool to extract this model; namely principal component analysis (PCA). This coding has very low complexity since encoding and decoding only consist of multiplication operations. The faces are treated as single encoding entities and all operations are performed on full images; no block processing is needed. These features mean that PCA coding can deliver high quality video at very low bitrates with low complexity for encoding and decoding. With the use of asymmetrical PCA (aPCA) it is possible to use only semantically important areas for encoding while decoding full frames or a different part of the frames. We show that a codec based on PCA can compress facial video to a bitrate below 5 kbps and still provide high quality. This bitrate can be delivered on a GSM network. We also show the possibility of extending PCA coding to encoding of high definition video.
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Suryadevara, Rajesh. "Visual perception based bit allocation for low bitrate video coding." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/40230.
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996. Includes bibliographical references (leaves 45-47). by Rajesh Suryadevara. M.S.
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Söderström, Ulrik. "Very low bitrate video communication : a principal component analysis approach /." Umeå : Department of Applied Physics and Electronics, Umeå University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1808.
The packing and coding of digital video is a part of science where much innovation has taken place during the last few decades. The MPEG standards of video encoding are some of the most well-known and used video coding standards today. Since MPEG defines exact requirements for the decoder, but not the encoder, encoders can be made in many different ways and levels of complexity, as long as they produce legal MPEG streams that can be viewed on any MPEG-conformant decoder. This thesis will examine the possible performance of MPEG, in particular MPEG-1/MPEG-2 full TV resolution (720*576), for coding video at bitrates significantly lower than the 2-15 Mb/s MPEG-2 originally was designed for. For this purpose, encoding methods previously proposed by various researchers are presented. Furthermore a few new algorithms, which can be used for MPEG coding in general, but was constructed with a low-bitrate encoder in mind, were developed. Finally objective video quality benchmarks were conducted and the results evaluated.
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Söderström, Ulrik. "Very low bitrate facial video coding : based on principal component analysis." Licentiate thesis, Umeå University, Applied Physics and Electronics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-895.
This thesis introduces a coding scheme for very low bitrate video coding through the aid of principal component analysis. Principal information of the facial mimic for a person can be extracted and stored in an Eigenspace. Entire video frames of this persons face can then be compressed with the Eigenspace to only a few projection coefficients. Principal component video coding encodes entire frames at once and increased frame size does not increase the necessary bitrate for encoding, as standard coding schemes do. This enables video communication with high frame rate, spatial resolution and visual quality at very low bitrates. No standard video coding technique provides these four features at the same time.
Theoretical bounds for using principal components to encode facial video sequences are presented. Two different theoretical bounds are derived. One that describes the minimal distortion when a certain number of Eigenimages are used and one that describes the minimum distortion when a minimum number of bits are used.
We investigate how the reconstruction quality for the coding scheme is affected when the Eigenspace, mean image and coefficients are compressed to enable efficient transmission. The Eigenspace and mean image are compressed through JPEG-compression while the while the coefficients are quantized. We show that high compression ratios can be used almost without any decrease in reconstruction quality for the coding scheme.
Different ways of re-using the Eigenspace for a person extracted from one video sequence to encode other video sequences are examined. The most important factor is the positioning of the facial features in the video frames.
Through a user test we find that it is extremely important to consider secondary workloads and how users make use of video when experimental setups are designed.
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Söderström, Ulrik. "Very low bitrate facial video coding : based on principal component analysis /." Umeå : Department of Applied Physics and Electronics, Umeå University, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-895.
Multi-view Video Coding (MVC) is vital for low bitrate applications that have constraints in bandwidth, battery capacity and memory size. Symmetric and mixed spatial-resolution coding approaches are addressed in this thesis, where Prediction Architecture (PA) is investigated using block matching statistics. Impact of camera separation is studied for symmetric coding to define a criterion for the best usage of MVC. Visual enhancement is studied for mixed spatial-resolution coding to improve visual quality for the interpolated frames by utilising the information derived from disparity compensation. In the context of symmetric coding investigations, camera separation cannot be used as a sufficient criterion to select suitable coding solution for a given video. Prediction architectures are proposed, where MVC that uses these architectures have higher coding performance than the corresponding codec that deploys a set of other prediction architectures, where the coding gain is up to 2.3 dB. An Adaptive Reference Frame Ordering (ARFO) algorithm is proposed that saves up to 6.2% in bits compared to static reference frame ordering when coding sequence that contains hard scene changes. In the case of mixed spatial-resolution coding investigations, a new PA is proposed that is able to save bitrate by 13.1 Kbps compared to the corresponding codec that uses the extended architecture based on 3D-digital multimedia. The codec that uses hierarchical B-picture PA has higher coding efficiency than the corresponding codec that employs the proposed PA, where the bitrate saving is 24.9 Kbps. The ARFO algorithm has been integrated with the proposed PA where it saves bitrates by up to 35.4 Kbps compared to corresponding codec that uses other prediction architectures. Visual enhancement algorithm is proposed and integrated within the presented PA. It provides highest quality improvement for the interpolated frames where coding gain is up to 0.9 dB compared to the corresponding frames that are coded by other prediction architectures.
Furman, D., and M. Porat. "On Content-Based Very Low Bitrate Video Coding." In Visual Content Processing and Representation, 260–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39798-4_33.
Lech, Piotr. "A Low Bitrate Video Transmission for IP Networks." In Advances in Intelligent Systems and Computing, 301–7. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10662-5_37.
Bartkowiak, Maciej, and Marek Domański. "Efficient representation of chrominance for very low bitrate coding." In Multimedia Applications, Services and Techniques — ECMAST'98, 415–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64594-2_112.
Zhao, Xin, Xinfeng Zhang, Li Zhang, Siwei Ma, and Wen Gao. "Low-Complexity and Sampling-Aided Multi-view Video Coding at Low Bitrate." In Advances in Multimedia Information Processing - PCM 2010, 319–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15696-0_30.
Chen, Chunxi, and Zhenrong Yang. "MPEG4 Compatible Video Browsing and Retrieval over Low Bitrate Channel." In Advances in Multimedia Information Processing — PCM 2002, 1221–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36228-2_151.
Mitrea, Mihai, Françoise Prêteux, and Mihai Petrescu. "Very Low Bitrate Video: A Statistical Analysis in the DCT Domain." In Visual Content Processing and Representation, 99–106. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11738695_14.
Chen, Si, Yuan Zhang, Huan Peng, and Jinyao Yan. "A Joint Bitrate and Buffer Control Scheme for Low-Latency Live Streaming." In Intelligence Science and Big Data Engineering. Big Data and Machine Learning, 369–80. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36204-1_31.
Cao, Li, Xiaoyun Zhang, and Zhiyong Gao. "An Efficient Optimization of Real-Time AVS+ Encoder in Low Bitrate Condition." In Communications in Computer and Information Science, 265–75. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4211-9_26.
Su, Yu-Chuan, Tzu-Hsuan Chiu, Yan-Ying Chen, Chun-Yen Yeh, and Winston H. Hsu. "Enabling low bitrate mobile visual recognition." In the 21st ACM international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2502081.2502110.
Lincoln, Luke, and Ruben Gonzalez. "Plane-Tree Low-Bitrate Mesh Compression." In 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2015. http://dx.doi.org/10.1109/dicta.2015.7371295.
Roger Cheuk, K. W., S. H. Gary Chan, K. W. Alice Mong, C. M. Martin Lee, and S. S. Shirley Sy. "DEVELOPING PDA FOR LOW-BITRATE LOW-DELAY VIDEO DELIVERY." In Proceedings of the Fifth IFIP-TC6 International Conference. WORLD SCIENTIFIC, 2003. http://dx.doi.org/10.1142/9789812791146_0041.
Winkler, Stefan, and Christof Faller. "Audiovisual quality evaluation of low-bitrate video." In Electronic Imaging 2005, edited by Bernice E. Rogowitz, Thrasyvoulos N. Pappas, and Scott J. Daly. SPIE, 2005. http://dx.doi.org/10.1117/12.596852.
Vaillancourt, Tommy, Vladimir Malenovsky, Redwan Salami, Zexin Liu, Lei Miao, Jon Gibbs, and Milan Jelinek. "Advances in low bitrate time-frequency coding." In ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7179106.
Aklouf, Mourad, Marc Leny, Frederic Dufaux, and Michel Kieffer. "Low Complexity Versatile Video Coding (VVC) for Low Bitrate Applications." In 2019 8th European Workshop on Visual Information Processing (EUVIP). IEEE, 2019. http://dx.doi.org/10.1109/euvip47703.2019.8946261.
Daskalakis, Spyridon Nektarios, George Goussetis, and Apostolos Georgiadis. "Low Bitrate Ambient FM Backscattering for Low Cost and Low Power Sensing." In 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC). IEEE, 2018. http://dx.doi.org/10.23919/ursi-at-rasc.2018.8471572.
Nam, Hyeong-Min, Byoung-Kyu Dan, Hye-Soo Kim, Jae-Yun Jeong, and Sung-Jea Ko. "Low Complexity H.264 Transcoder for Bitrate Reduction." In 2006 International Symposium on Communications and Information Technologies. IEEE, 2006. http://dx.doi.org/10.1109/iscit.2006.340020.
