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Deep social force network for anomaly event detection

IET image PROCESSING 2021年第14期15卷 3441-3453页

作者： Yang, Xingming Wang, Zhiming Wu, Kewei Xie, Zhao Hou, Jinkui Hefei Univ Technol Minist Educ Key Lab Knowledge Engn Big Data Hefei 230601 Peoples R China Hefei Univ Technol Anhui Prov Key Lab Affect Comp & Adv Intelligent Hefei Peoples R China Hefei Univ Technol Sch Comp Sci & Informat Engn Hefei Peoples R China Weifang Univ Sch Comp Engn Weifang 261061 Peoples R China

Anomaly event detection is vital in surveillance video analysis. However, how to learn the discriminative motion in the crowd scene is still not tackled. Here, a deep social force network by exploiting both social force extracting and deep motion coding is proposed. Given a grid of particles with velocity provided by the optical flow, the interaction force in the crowd scene is investigated and a social force module is embedded in a deep network. A deep motion convolution was further designed with a 3D (DMC-3D) module. The DMC-3D not only eliminates the noise motion in the crowd scene with a spatial encoder-decoder but also learns the 3D feature with a spatio-temporal encoder. The deep social force coding is modelled with multiple features, in which each feature can describe specific anomaly motion. The experiments on UCF-Crime and ShanghaiTech datasets demonstrate that our method can predict the temporal localization of anomaly events and outperform the state-of-the-art methods.

关键词： image and video coding image recognition Computer vision and image processing techniques video signal processing Data handling techniques Neural nets

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Real-time low-bitrate multimedia communication for smart spaces and wireless sensor networks

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IET COMMUNICATIONS 2011年第17期5卷 2482-2490页

作者： Vijayanagar, K. R. Kim, J. IIT Dept Elect & Comp Engn Chicago IL 60616 USA

Smart spaces is a scenario that is ideal for the application of wireless communication technology to benefit non-expert users. A prime example of such an application would be low-cost and real-time video surveillance of hallways or video conferencing. Traditional solutions for these scenarios use state-of-the-art video codecs like H.264/AVC in order to achieve the low bitrate which is essential in wireless communication. On the flip side, such encoders are computationally complex and need expensive hardware to run on thus making them inefficient choices for being deployed in clusters. Recent research has resulted in distributed video coding (DVC) being proposed as a solution for applications that have limited battery resources and low hardware complexity, thus necessitating a low-complexity encoder. It is now a popular topic in the research community and the past years have seen several implementations. However, current DVC solutions use iteratively decodable channel codes like low-density parity check - accumulate (LDPCA) codes or Turbo codes that have large latencies. In order to make real-time communication possible, the proposed architecture makes efficient use of skip blocks to reduce the bitrate, eliminates the iterative decoding nature of the Wyner-Ziv (WZ) channel and uses a simple data-hiding-based compression algorithm. This drastically cuts down on the time complexity of the decoding procedure while still maintaining a rate-distortion performance better than that of H.264/AVC intra-coding and other current DVC solutions.

关键词： image and video coding LDPCA code video codecs WZ channel smart space real-time low-bitrate multimedia communication simple data-hiding-based compression algorithm H.264-AVC intracoding video coding Wireless sensor networks decoding DVC channel coding wireless sensor network multimedia communication iterative decoding nature distributed video coding video codec wireless sensor networks video conferencing low-complexity encoder decodable channel code video surveillance Wyner-Ziv channel image recognition Multimedia communications wireless communication technology turbo code rate-distortion performance low-density parity check-accumulate code

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Feature fusion quality assessment model for DASH video streaming

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IET image PROCESSING 2021年第1期15卷 127-142页

作者： Zhang, Hong Li, Fan Yan, Zhisheng Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian 710049 Shaanxi Peoples R China Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA

Dynamic Adaptive Streaming over HTTP (DASH) employs the flexible rate adaptation scheme to combat with time-varying channel conditions. In addition to compression impairment, DASH video streaming suffers from transmission impairment, such as rate switches and stalling events. Both of them severely degrade users' Quality of Experience (QoE). Herein, an assessment model is established for DASH video streaming by directly jointing multiple QoE influential factors, which quantify impairments resulting from the compression and transmission. To demonstrate the influence of video content characteristics on users' QoE, spatio-temporal content perceptual features are employed to represent the compression impairment. When reflecting temporal characteristics, a novel motion vector padding method is proposed to quantify the influence of intra macroblock on the human visual system. The proposed model is evaluated on a newly public Waterloo SQoE-III database, which is available for DASH video streaming. Experimental results demonstrate that the authors' model outperforms the comparative models and owns the strong generalization ability to different video contents. Moreover, the proposed model is statistically superior to the existing models.

关键词： image and video coding Multimedia communications Computer vision and image processing techniques video signal processing

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Fast motion estimation approaches for surveillance-type videos in an inter-frame JPEG 2000-based adaptive video coding system

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IET image PROCESSING 2012年第1期6卷 31-42页

作者： Schuchter, A. Uhl, A. Salzburg Univ Dept Comp Sci A-5020 Salzburg Austria

In this study, we evaluate fast motion estimation (ME) techniques in the context of a JPEG 2000-based video coding system for surveillance-type videos. The authors have designed a low-complexity algorithm, called block-selective ME, which restricts block matching to certain frames or blocks containing high motion. They compare the performance of our block-selective ME algorithm to a frame-based approach and to a standard fast-motion algorithm (three-step search (TSS)). For surveillance-type videos, the authors show that the block-selective approach achieves the peak signal to noise ratio (PSNR) quality of a full ME scheme for;70-80% of the blocks. Moreover, this approach delivers a higher visual image quality compared to TSS, if the computational load for a set number of blocks were fixed. The authors have integrated our block-selective approach into different coders (H.264 and MPEG-2) and show that our approach is an outstanding alternative to fast-ME in low-complexity environments.

关键词： search problems visual image quality three-step search algorithm image recognition adaptive video coding system image and video coding surveillance-type videos fast-motion algorithm motion estimation adaptive codes interframe JPEG 2000 image matching block matching video coding image sequences video surveillance peak signal to noise ratio low-complexity algorithm block-selective ME algorithm Computational complexity video signal processing video frames computational complexity Combinatorial mathematics PSNR

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Approximately even partition algorithm for coding the Hilbert curve of arbitrary-sized image

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IET image PROCESSING 2012年第6期6卷 746-755页

作者： Wu, C-C. Chang, Y-I. Natl Sun Yat Sen Univ Dept Comp Sci & Engn Kaohsiung 80424 Taiwan

The Hilbert curve is one of space filling curves and it requires that the region is of size 2(k) x 2(k), where k is an element of N. This study relaxes this constraint and generates a pseudo-Hilbert curve of arbitrary dimension. The intuitive method such as Chung et al.'s algorithm is to use Hilbert curves in the decomposed areas directly and then have them connected. However, they must generate a sequence of the scanned quadrants additionally before encoding and decoding the Hilbert order of one pixel. In this study, by using the approximately even partition approach, the authors propose a new Hilbert curve, the Hilbert* curve, which permits any square regions. Experimental results show that the clustering property of the Hilbert* curve is similar to that of the standard Hilbert curve. Next, the authors also propose encoding/decoding algorithms for the Hilbert* curves. Since the authors do not need to additionally generate and scan the sequence of quadrants, the proposed algorithm outperforms Chung et al.'s algorithms for the square region. Then, the authors apply the Hilbert* curves in Chung et al.'s algorithms for the Hilbert curve of arbitrary dimension and experimental results show that the proposed encoding/decoding algorithms out perform the Chung et al.'s approach.

关键词： space filling curves Computer vision and image processing techniques scanned quadrants image and video coding decoding algorithms arbitrary dimension image coding pseudoHilbert curve Hilbert transforms arbitrary sized image Integral transforms in numerical analysis approximately even partition algorithm decoding clustering property

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Compressive sensing reconstruction of hyperspectral images based on codec space-spectrum joint dense residual network

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IET image PROCESSING 2023年第3期17卷 916-931页

作者： Xiao, Shuming Zhang, Ye Chang, Xuling Xu, Jiajia Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys 3888 Dong Nanhu Rd Changchun 130033 Peoples R China Univ Chinese Acad Sci Daheng Coll Beijing 100000 Peoples R China Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Changchun Peoples R China

The spatial and spectral information contained in the hyperspectral image (HSI) make it widely used in many fields. However, the sharp increase of HSI data brings enormous pressure to the data storage and real-time transmission. The research shows that hyperspectral compressive sensing (HCS) breaks through the bottleneck of the Nyquist sampling theorem, which can relieve the massive pressure on data storage and real-time transmission. Existing HCS methods try to design advanced compression sampling matrix or reconstruction algorithms, but cannot connect the two through a unified framework. To further improve the image reconstruction quality, a novel codec space-spectrum joint dense residual network (CDS2-DResN) is proposed. The CDS2-DResN is divided into block compression sampling part and reconstruction part. For block compression sampling, coded convolutional layer (CCL) is leveraged to compress and sample HSI. For measurements reconstruction, deconvolution layer is first leveraged to initially reconstruct HSI, and then build a space-spectrum joint network to refine the initial reconstructed HSI. Moreover, the CCL and reconstruction network are optimized via a unified framework, which can simplify the pre-processing and post-processing process of HCS. Extensive experiments have shown that CDS2-DResN has an excellent HCS reconstruction effect at measurement rates 0.25, 0.10, 0.04 and 0.01, respectively.

关键词： feature extraction block compression sampling part Nyquist sampling theorem hyperspectral image compression sampling matrix massive pressure Geophysics computing CDS2-DResN enormous pressure initial reconstructed HSI reconstruction network image and video coding Neural nets geophysical image processing coded convolutional layer Optical, image and video signal processing Computer vision and image processing techniques convolutional neural nets measurements reconstruction compressed sensing hyperspectral imaging compressive sensing reconstruction Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research reconstruction part HSI data excellent HCS reconstruction effect hyperspectral compressive sensing sample HSI image reconstruction space-spectrum joint network spatial information Geophysical techniques and equipment real-time transmission spectral information novel codec space-spectrum joint dense residual network image reconstruction quality data storage HCS methods

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Perceptually weighted optical flow for motion-based segmentation in MPEG-4 paradigm

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ELECTRONICS LETTERS 2000年第20期36卷 1693-1694页

作者： Malo, J Gutierrez, J Epifanio, I Ferri, FJ Univ Valencia Dept Opt Valencia 46100 Spain Univ Valencia Dept Informat Valencia 46100 Spain

In the MPEG-4 paradigm, the sequence must be described in terms of meaningful objects. This meaningful, high-level, representation should emerge from low-level primitives such as optical flow and prediction error which are the basic elements of previous-generation video coders. The accuracy of the high-level models strongly depends on the robustness of the primitives used. It is shown how perceptual weighting in optical flow computation gives rise to better motion estimates which consistently improve motion-based segmentation compared to equivalent unweighted motion estimates.

关键词： motion estimation MPEG-4 paradigm image and video coding image segmentation prediction error low-level primitives perceptually weighted optical flow video signal processing high-level representation robustness video coders video coding image sequences motion-based segmentation

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Oblivious robust watermarking method by image pre-processing

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ELECTRONICS LETTERS 2002年第14期38卷 702-704页

作者： Agung, IW Sweeney, P Univ Surrey CCSR Guildford GU2 7XH Surrey England

A method of image watermarking which requires no original image for detection is introduced. The proposed scheme pre-processes the original image and embeds the watermark in some parts of the transform coefficients. I... 详细信息

关键词： message authentication watermark embedding Integral transforms in numerical analysis image and video coding copy protection oblivious watermarking method image coding digital watermark transform coefficients robust watermarking method discrete cosine transforms Computer vision and image processing techniques image pre-processing DCT coefficients

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image scrambling through a fractional GF(qⁿ) composite domain

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ELECTRONICS LETTERS 2001年第11期37卷 685-687页

作者： Sun, YS Shyu, HC Chung Cheng Inst Technol Dept Elect Engn Tao Yuan Taiwan

A novel fractional GF(q(n)) composite domain (FGCD) for image scrambling applications is described. The FGCD scrambled image can be recovered using the appropriate keys without any knowledge of the original image info... 详细信息

关键词： image information image and video coding copy protection reversing performance Computer vision and image processing techniques image coding FGCD scrambled image fractional GF(qn) composite domain Gaussian noise image scrambling Other topics in statistics

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Optimisation-based placement of resynchronisation markers for error robust video transmission

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ELECTRONICS LETTERS 2001年第6期37卷 348-350页

作者： Lee, SH Kim, JK Korea Adv Inst Sci & Technol Dept Elect Engn & Comp Sci Taejon South Korea

A novel method for placement of resynchronisation markers for error robust video transmission is proposed. Given the number of markers assigned to the current frame, marker positions are decided in a rate-distortion o... 详细信息

关键词： error robust video transmission current frame rate distortion theory image and video coding Viterbi decoding optimisation-based placement resynchronisation markers Viterbi algorithm Codes synchronisation marker positions video signal processing Signal processing theory video coding rate-distortion optimal sense

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