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检索条件"任意字段=Conference on Real-Time Image and Video Processing 2011"

共 8693 条记录，以下是91-100 订阅

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Abnormal Activity Detection Using video Action Recognition: A Review 6

Abnormal Activity Detection Using Video Action Recognition: ...

引用

6th International conference on Natural Language processing (ICNLP)

作者： Ojha, Abhushan Liu, Ying Hao, Yu Xian Univ Posts & Telecommun Ctr Image & Informat Proc Xian Peoples R China

ISBN: (纸本)9798350349122;9798350349115

The escalating ubiquity of video surveillance systems in both public and private sectors underscores an urgent need for automated mechanisms capable of identifying anomalous behaviors. Traditional methods, largely heuristic in nature, are increasingly being supplanted by neural network-based approaches, offering a more nuanced and effective means for anomaly detection in video data. While Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) have been extensively investigated, the incipient exploration of Transformer models in this domain represents a compelling research frontier. Transformer models, while beneficial, face challenges like computational intensity and data requirements. This paper presets the comparative analysis of deep learning for Abnormal activity detection. In our study, we assess the strengths and weaknesses of widely-used methods, considering both their structural features and their practical effectiveness in experiments. Additionally, we present an examination of emerging research avenues and potential future endeavors. Future directions should focus on optimizing neural architectures and transformers for real-time analytics, addressing skewed data, and establishing ethical guidelines for automated surveillance. It calls for interdisciplinary studies on the ethical implications of automated anomaly detection, setting the stage for enhancing Transformer models in real-time surveillance and evaluating their resilience against adversarial attacks.

关键词： abnormal activity detection convolutional neural network recurrent neural network transformers video action recognition

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real-time FPGA Implementation of the Semi-global Matching Stereo Vision Algorithm for a 4K/UHD video Stream 16th

Real-Time FPGA Implementation of the Semi-global Matching St...

引用

16th International Workshop on Design and Architecture for Signal and image processing (DASIP) held jointly with the 18th HiPEAC conference

作者： Grabowski, Mariusz Kryjak, Tomasz AGH Univ Sci & Technol Dept Automat Control & Robot Comp Vis Lab Embedded Vis Syst Grp Krakow Poland

ISBN: (纸本)9783031299698;9783031299704

In this paper, we propose a real-time FPGA implementation of the Semi-Global Matching (SGM) stereo vision algorithm. The designed module supports a 4K/Ultra HD (3840 x 2160 pixels @ 30 frames per second) video stream in a 4 pixel per clock (ppc) format and a 64-pixel disparity range. The baseline SGM implementation had to be modified to process pixels in the 4ppc format and meet the timing constrains, however, our version provides results comparable to the original design. The solution has been positively evaluated on the Xilinx VC707 development board with a Virtex-7 FPGA device.

关键词： SGM FPGA 4K Ultra HD real-time processing stereo vision

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Research on visual monitoring of natural gas leak based on spectral video technology

Research on visual monitoring of natural gas leak based on s...

引用

2024 International conference on Computer Vision and image processing, CVIP 2024

作者： Min, Haipeng Xiao, Jinguang Zu, Yongxiang Yang, Kai Wang, Chong Shaanxi Gas Group Co. Ltd. Xi’an Economic and Technological Development No. 2 Kaiyuan Road A1 Zone Zone Xi’an710016 China Nanjing Zhipu Technology Co. Ltd. Nanjing UASP Building 4 No. 8 Yuanhua Road Qixia District Nanjing210000 China

ISBN: (纸本)9781510688384

This paper introduces a natural gas visualization and leak monitoring system based on spectral video technology. The system combines multiple modalities, including spectral video imaging, laser scanning, and visible light camera, to achieve efficient detection and precise localization of gas leaks. The system can detect, quantify, and report gas leaks in real-time. Results indicate that the system offers high detection sensitivity and accuracy in detecting leaks within complex environments, providing reliable assurance for the safe operation of chemical plants. © 2025 SPIE.

关键词： Chemical Safety Environmental Monitoring Gas Leak Monitoring Multi-sensor Fusion

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Optimized Hardware Architecture of Tile to Raster Scan Buffer for video Decoder and Display Processor

Optimized Hardware Architecture of Tile to Raster Scan Buffe...

引用

IEEE International conference on Consumer Electronics (ICCE)

作者： Seong, Han-Soo Jung, Choonsik Samsung Elect Co Ltd Hwasung South Korea

ISBN: (纸本)9781665491303

As market is driving larger-sized TVs and display devices, video compression codec and video image processing algorithm are being developed with higher (4K to 8K) video resolution. It is critical to implement an optimized display system to satisfy the increasing needs for external memory bandwidth. In this paper, we propose an optimized hardware architecture of tile to raster scan line buffer. The tile to raster scan line buffer converts the video image data stored in tiled format to the raster scan order for display devices. Using the pattern of tile to raster scan order, the double buffering used by conventional system is removed and a simplified buffer access algorithm for real-time hardware implementation is proposed. The proposed method reduces buffer size by 50% compared to the conventional architecture.

关键词： TV image resolution image coding Memory management Bandwidth Streaming media video compression

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FPGA-ACCELERATED HEVC ENCODER FOR ENERGY-EFFICIENT MULTI-ACCESS EDGE COMPUTING 30

FPGA-ACCELERATED HEVC ENCODER FOR ENERGY-EFFICIENT MULTI-ACC...

引用

30th IEEE International conference on image processing (ICIP)

作者： Sjovall, Panu Mercat, Alexandre Vanne, Jarno Tampere Univ Ultra Video Grp Tampere Finland

ISBN: (纸本)9781728198354

High Efficiency video Coding (HEVC) and Multi-access Edge Computing (MEC) technologies can make real-time streaming media services available to users with reasonable bandwidth, but the computational complexity of HEVC tends to lead to increased energy consumption in these schemes. In this paper, we investigate the energy saving opportunities of utilizing a field-programmable gate array (FPGA) based HEVC encoder in edge media servers and devices. In practice, we analyze the energy impact of migrating our Kvazaar software HEVC intra encoder to Intel Arria 10 PCIe FPGA(s) on two platforms: 1) Nokia Airframe Cloud Server with 2.4 GHz dual 14-core Intel Xeon processors and 2) an embedded Jetson AGX Orin board with 2.2 GHz 12-core ARM processor. According to our experiments, FPGA encoding on these two platforms saved 76% and 86% of the energy taken up by software only encoding on Airframe, respectively. These results indicate the potential of FPGA-based video encoder acceleration in future green MEC architectures.

关键词： High Efficiency video Coding (HEVC/H.265) Kvazaar HEVC encoder field-programmable gate array (FPGA) energy efficiency Multi-access Edge Computing (MEC)

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FLOW-GUIDED DEFORMABLE ATTENTION NETWORK FOR FAST ONLINE video SUPER-RESOLUTION 30

FLOW-GUIDED DEFORMABLE ATTENTION NETWORK FOR FAST ONLINE VID...

引用

30th IEEE International conference on image processing (ICIP)

作者： Yang, Xi Zhang, Xindong Zhang, Lei Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China

ISBN: (纸本)9781728198354

real-time online video super-resolution (VSR) on resource limited applications is a very challenging problem due to the constraints on complexity, latency and memory footprint, etc. Recently, a series of fast online VSR methods have been proposed to tackle this issue. In particular, attention based methods have achieved much progress by adaptively aligning or aggregating the information in preceding frames. However, these methods are still limited in network design to effectively and efficiently propagate the useful features in temporal domain. In this work, we propose a new fast online VSR algorithm with a flow-guided deformable attention propagation module, which leverages corresponding priors provided by a fast optical flow network in deformable attention computation and consequently helps propagating recurrent state information effectively and efficiently. The proposed algorithm achieves state-of-the-art results on widely-used benchmarking VSR datasets in terms of effectiveness and efficiency. Code can be found at https://***/IanYeung/FastOnlineVSR.

关键词： video super-resolution Flow-guided deformable attention Deep neural networks

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High Resolution Panoramic video Synthesis and Objects Detection on Panoramic video 4

High Resolution Panoramic Video Synthesis and Objects Detect...

引用

4th International conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2024

作者： Romanova, Karina E. Tsybulko, Evgeniya A. Rudenko, Danila I. Khelvas, Aleksandr V. Gilya-Zetinov, Aleksandr A. Tykhonov, Illya V. Mipt Moscow Russia Intc Intelligent Electronics-Valdai Veliky Novgorod Russia Cos&ht Dolgoprudnii Russia Soccos Moscow Russia Ipmce Moscow Russia

ISBN: (纸本)9798350309508

We propose an approach to the creation of a panorama viewport and objects detection within it in real-time on the base of the set of videos from the assembly of cameras. The task of the panorama viewport generation is significantly different from the panoramic image generation. We perform image stitching only with a part of cameras views (region of interest - ROI) and display the resulting images flow on the user's screen. The complexity of this problem is in processing the images from the set of cameras at the moment, since it is impossible to stitch, process and save the whole panorama in the user device memory. The main practical application of the proposed technology is video surveillance for transportation, industry and public objects (airports, railway stations, sea and river ports, plants, stadiums, etc.). Nowadays, there are many scientific articles exploring panorama stitching methods. However, not many existing algorithms can be used for the panorama stitching in real-time as is. real-time panorama stitching is the value of the proposed approach. © 2024 IEEE.

关键词： Computer vision

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STDF-DSCS: A Lightweight Scheme for Compressed video Quality Enhancement 16

STDF-DSCS: A Lightweight Scheme for Compressed Video Quality...

引用

16th International conference on Wireless Communications and Signal processing, WCSP 2024

作者： Pei, Shufan Ren, Guangming Zhao, Tiesong Lin, Liqun Fuzhou University Fuzhou China

ISBN: (纸本)9798350390643

Lossy compression reduces the data amount in the video by sacrificing quality, which leads to severe distortion, especially when videos are overly compressed. Con-sequently, many restoration methods have been proposed to repair compressed videos. However, they are limited by their substantial computational demand and complexity. To conserve computational resources and enhance real-time capabilities, we implement a compressed video enhancement method based on Spatio-Temporal Deformable Fusion (STDF) and subsequently design a lightweight scheme for it. By integrating depthwise separable convolution and channel shuffle techniques, we design a lightweight version of STDF called STDF-DSCS. STDF-DSCS reduces computational complexity and improves model inference speed while maintaining enhancement quality. The depthwise separable convolution reduces the model's computational complexity, while channel shuffle compensates for the shortcomings of group convolution, enhancing inter-channel communication and the network's feature learning capability. Extensive experiments demonstrate that STDF-DSCS significantly enhances computational efficiency while maintaining comparable enhancement effects to existing methods, which can be utilized in real-time video processing scenarios. © 2024 IEEE.

关键词： image reconstruction

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A Deep Learning Approach for Multiple Weather Conditions Detection Based on In-Vehicle Dash Camera video

A Deep Learning Approach for Multiple Weather Conditions Det...

引用

ASCE International conference on Transportation and Development (ICTD)

作者： Li, Lizhe Ahmed, Mohamed M. Univ Cincinnati Dept Civil & Architectural Engn & Construct Manag Cincinnati OH 45221 USA

ISBN: (纸本)9780784485514

Weather conditions significantly influence traffic safety, with adverse conditions often leading to hazardous driving environments. This study presents the development of a weather detection model based on convolutional neural networks (CNNs), specifically trained on in-vehicle dash camera videos. Using thousands of images sourced from the SHRP2 trajectories level dataset, seven distinct weather categories were identified: clear, light snow, heavy snow, light rain, heavy rain, distant fog, and near fog. For enhanced training efficiency, images were strategically segmented. An innovative approach was employed where, on average, nine images were selected from every minute of the video;these images underwent processing using various pre-trained CNN architecture, such as "AlexNet," "GoogleNet," "ResNet," among others. The predominant detection results then informed the overall weather condition for the given video segment. The model exhibited promising performance, underscoring its viability for real-time in-vehicle weather detection and consequent enhancement of road safety.

关键词： image enhancement

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NN-based decision predictor of picture resolution change for video coding 47

NN-based decision predictor of picture resolution change for...

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conference on Applications of Digital image processing XLVII

作者： Guermoud, Hassane Bordes, Philippe Galpin, Franck Dumas, Thierry Reuze, Kevin Francois, Edouard Rath, Gagan Tescher, Andrew G. Ebrahimi, Touradj Video Lab InterDigital Res & Innovat 975 Ave Champs Blancs F-35576 Cesson Sevigne France

ISBN: (纸本)9781510679344;9781510679351

Reference Picture Resampling (RPR) is a powerful tool that allows improving video coding efficiency of next generation codecs like Versatile video Coding (VVC) or Enhanced Compression Model (ECM). This feature is well designed to support frame changing resolution without inserting an instantaneous decoder refresh (IDR) or intra random access picture (IRAP). video streaming and low delay scenarios can take advantage of RPR to ensure a smooth frame-based bit-rate adaptation, compared to traditional techniques that can generate bitrate leaps. This paper proposes an encoder method to select the picture resolution change parameters effectively depending on the video signal characteristics. The picture resolution change decision is based on a low complexity neural network, and it is performed before the encoding process without RD-score computations making this approach suitable for real time and low delay implementation. The experiments under Random Access (RA) and All Intra (AI) configurations of the VVC Test Model (VTM-21.1) show that the proposed method can bring luma BD-rate gain improvement of 1.46% and 0.95% respectively compared to the VVC Test Model anchor.

关键词： video Coding Reference Picture Re-sampling Adaptive Resolution Coding Neural Network Versatile video Coding

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