With the development of urbanization, traffic problems are becoming more and more serious. Relevant literature shows that traffic information is a direct reflection of road conditions, and timely mastering of traffic ...
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There has been a rise in the frequency of fire-related calamities all over the globe, which leads to the need for an efficient fire detection system to avoid high losses or fatalities. This paper focuses on real-time ...
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ISBN:
(数字)9798350378092
ISBN:
(纸本)9798350378108
There has been a rise in the frequency of fire-related calamities all over the globe, which leads to the need for an efficient fire detection system to avoid high losses or fatalities. This paper focuses on real-time fire detection techniques through image and videoprocessing. In particular, this paper is aimed at a color detection approach that uses HSV and YCbCr color models for detecting only fire pixels along with the implementation of fire movement detection approach by comparing consecutive frames from the live feed. Overall, the study contributes to advancing fire detection methodology, highlighting the potential of imageprocessing methods in real-time fire detection systems.
In the pursuit of effective real-timevideo transmission for First-Person View (FPV) drone systems, optimizing the encoding process is paramount. Traditional encoding methods, reliant on pre-encoding demosaicking, oft...
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In the pursuit of effective real-timevideo transmission for First-Person View (FPV) drone systems, optimizing the encoding process is paramount. Traditional encoding methods, reliant on pre-encoding demosaicking, often fall short in balancing the trade-off between video quality and latency, essential for seamless real-time feedback. This work proposes a novel approach by deferring the demosaicking process to the decoder side, thereby encoding the rearranged Bayer pattern (RGGB) data directly. This deferment significantly reduces the input data size, to the tune of a threefold reduction, thereby achieving a more expeditious encoding process. The tailored encoder and decoder architecture ensures the accurate reconstruction of the full-color image on the decoder side. Through a comprehensive evaluation, leveraging a specialized video quality assessment framework designed for FPV drone footage, our findings illuminate the substantial benefits of our proposed method. Specifically, it achieves faster encoding times and reduced computational overhead, pivotal for low-latency applications. Furthermore, this study opens avenues for integrating advanced encoding techniques into commercial FPV drone systems, potentially enriching user experiences across various applications. Our research not only addresses a critical gap in real-timevideo transmission but also sets the stage for future exploration into optimizing encoding methodologies for the next generation of FPV drone technologies.
. image detail enhancement is critical to the performance of short-wave infrared (SWIR) imaging systems. Recently, the requirement for real-timeprocessing of high-definition (HD) SWIR video has shown rapid growth. Ne...
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. image detail enhancement is critical to the performance of short-wave infrared (SWIR) imaging systems. Recently, the requirement for real-timeprocessing of high-definition (HD) SWIR video has shown rapid growth. Nevertheless, the research on field programmable gate array (FPGA) implementation of HD SWIR streaming videoprocessing architecture is relatively few. This work proposes a real-time FPGA architecture of SWIR video enhancement by combining the difference of Gaussian filter and plateau equalization. To accelerate the algorithm and reduce memory bandwidth, two efficient key architectures, namely edge information extraction and equalization and remapping architecture, are proposed to sharpen edges and improve dynamic range. The experimental results demonstrated that the proposed architecture achieved a real-timeprocessing of 1280 x 1024@60Hz with 2.7K lookup tables, 2.5K Slice Reg, and about 350 kb of block RAM consumption, and their utilization reached 12.5%, 19.2%, and 12.5% for the XC7A200T FPGA board, respectively. Moreover, the proposed architecture is fully pipelined and synchronized to the pixel clock of output video, meaning that it can be seamlessly integrated into diverse real-timevideoprocessing systems.
image dehazing is a crucial task in the early stages of real-timeimageprocessing pipelines used in applications such as surveillance and advance driver assistance systems. Dehazing algorithms mitigate the spatially ...
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image dehazing is a crucial task in the early stages of real-timeimageprocessing pipelines used in applications such as surveillance and advance driver assistance systems. Dehazing algorithms mitigate the spatially selective degradation of image details caused by natural phenomenon such as fog and sandstorms. The problem is exacerbated in the presence of color cast which can affect the color-sensitive processing in the downstream tasks. In order to correct these two aberrations, we have proposed a light-weight algorithm which is not only quantitively more effective than the state-of-the-art works but also uses minimal computational resources. Specifically, it has been proposed to tackle both aforementioned problems by processing luminance and chrominance channels separately through a custom resource-efficient colorspace transform. Moreover, it has been proposed to employ online calculation of the relevant video stream statistics to estimate the degradation model over several temporally adjacent frames. This approach not only reduces the hardware resource utilization when implemented inside the videoprocessing pipeline but also reduces the flicker effect observed when frames are processed individually. It has been demonstrated through quantitative analysis on standard datasets that the proposed approach either works at par or better than the reference works in terms of image quality metrics. Furthermore, the proposed framework has been developed as a real-timevideoprocessing system on an FPGA platform. The synthesis results of this implementation suggest that the proposed framework achieves this performance using minimal logic resources.
In this study, we implemented a real-timevideo avatar generation method using imageprocessing and machine learning to develop a new advanced communication tool that enables information sharing and decision-making. U...
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In this study, we implemented a real-timevideo avatar generation method using imageprocessing and machine learning to develop a new advanced communication tool that enables information sharing and decision-making. Using the proposed method, users can easily send their real-timevideo avatars to the metaverse. We evaluated a questionnaire survey on 12 subjects to evaluate the effectiveness of the proposed real-timevideo avatar generation method. This evaluation was conducted based on the sense of being in the same room, degree of concentration, degree of communication of non-verbal information, ease of timing utterances and naturalness of conversation for 12 subjects. The 12 subjects held discussions using video conferencing and our proposed metaverse conferencing systems with real-timevideo avatars and answered some evaluation questionnaires. The evaluation results revealed that our proposed metaverse conferencing system using real-timevideo avatars is superior to the video conferencing system in all evaluation items.
This paper presents a real-time semantic video communication method for general scenes, combining lossy semantic map coding with motion compensation to achieve reduced bit rates while maintaining perceptual and semant...
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ISBN:
(纸本)9798350349405;9798350349399
This paper presents a real-time semantic video communication method for general scenes, combining lossy semantic map coding with motion compensation to achieve reduced bit rates while maintaining perceptual and semantic quality. Our findings show that semantic image synthesis effectively adapts to minute errors resulting from motion estimation, eliminating the need to transmit the residuals. We recommend the Group of Pictures approach as a more efficient alternative. Comparative assessments against HEVC and VVC confirm the method's effectiveness. This research paves the way for efficient real-time semantic video communication, addressing the demands of data-intensive visual applications.
An intelligent retrievable object-tracking system assists users in quickly and accurately locating lost objects. However, challenges such as real-timeprocessing on edge devices, low image resolution, and small-object...
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An intelligent retrievable object-tracking system assists users in quickly and accurately locating lost objects. However, challenges such as real-timeprocessing on edge devices, low image resolution, and small-object detection significantly impact the accuracy and efficiency of video-stream-based systems, especially in indoor home environments. To overcome these limitations, a novel real-time intelligent retrievable object-tracking system is designed. The system incorporates a retrievable object-tracking algorithm that combines DeepSORT and sliding window techniques to enhance tracking capabilities. Additionally, the YOLOv7-small-scale model is proposed for small-object detection, integrating a specialized detection layer and the convolutional batch normalization LeakyReLU spatial-depth convolution module to enhance feature capture for small objects. TensorRT and INT8 quantization are used for inference acceleration on edge devices, doubling the frames per second. Experiments on a Jetson Nano (4 GB) using YOLOv7-small-scale show an 8.9% improvement in recognition accuracy over YOLOv7-tiny in video stream processing. This advancement significantly boosts the system's performance in efficiently and accurately locating lost objects in indoor home settings.
This paper presents a demonstration setup for our open-source intra encoder called uvgVPCCenc, which is optimized for real-timevideo-based Point Cloud Compression (V-PCC). uvgVPCCenc achieves an average encoding spee...
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ISBN:
(纸本)9798331529543;9798331529550
This paper presents a demonstration setup for our open-source intra encoder called uvgVPCCenc, which is optimized for real-timevideo-based Point Cloud Compression (V-PCC). uvgVPCCenc achieves an average encoding speed of 26 frames per second (fps) on an Intel i7-12700 CPU when encoding volumetric video sequences with up to 185 000 points per frame. It is shown to be 700 times as fast as TMC2 reference implementation for V-PCC. Our work is the first to demonstrate real-time intra V-PCC encoding on a consumer-grade desktop computer. It indicates that even the immense computational complexity of intra V-PCC encoding can be tackled for practical applications with effective design and optimization techniques.
In this paper, we present a successful implementation of a local maxima filter on a Zybo Z7-20 and PYNQ Z1 FPGA using their two HDMI ports in real-time. The proposed system uses the HDMI ports to capture video frames ...
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ISBN:
(纸本)9798350367331;9798350367348
In this paper, we present a successful implementation of a local maxima filter on a Zybo Z7-20 and PYNQ Z1 FPGA using their two HDMI ports in real-time. The proposed system uses the HDMI ports to capture video frames with a resolution of 640x480 pixels. The local maxima filter is then applied to the captured frames in real-time, allowing for the detection of peaks in the image data. The filter uses a sliding window approach to determine the local maxima, and a threshold value is set to identify and retain only the most significant peaks in the image. The system was implemented using SystemVerilog Hardware Description Language (HDL). The system was developed in the Xilinx Vivado design suite and the results show that the proposed system is able to process video frames at a rate of 60 frames per second with high accuracy and low latency. The proposed implementation using SystemVerilog presents a more efficient and flexible solution for imageprocessing applications on FPGA, making it a promising approach for real-timeimageprocessing.
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