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image to image Translation Based on differential image Pix2Pix Model

Computers, Materials & Continua 2023年第10期77卷 181-198页

作者： Xi Zhao Haizheng Yu Hong Bian College of Mathematics and System Sciences Xinjiang UniversityUrumqi830017China School of Mathematical Sciences Xinjiang Normal UniversityUrumqi830017China

In recent years,Pix2Pix,a model within the domain of GANs,has found widespread application in the field of image-to-image ***,traditional Pix2Pix models suffer from significant drawbacks in image generation,such as the loss of important information features during the encoding and decoding processes,as well as a lack of constraints during the training *** address these issues and improve the quality of Pix2Pixgenerated images,this paper introduces two key ***,to reduce information loss during encoding and decoding,we utilize the U-Net++network as the generator for the Pix2Pix model,incorporating denser skip-connection to minimize information ***,to enhance constraints during image generation,we introduce a specialized discriminator designed to distinguish differential images,further enhancing the quality of the generated *** conducted experiments on the facades dataset and the sketch portrait dataset from the Chinese University of Hong Kong to validate our proposed *** experimental results demonstrate that our improved Pix2Pix model significantly enhances image quality and outperforms other models in the selected ***,the Pix2Pix model incorporating the differential image discriminator exhibits the most substantial improvements across all *** analysis of the experimental results reveals that the use of the U-Net++generator effectively reduces information feature loss,while the Pix2Pix model incorporating the differential image discriminator enhances the supervision of the generator during *** of these enhancements collectively improve the quality of Pix2Pix-generated images.

关键词： image-to-image translation generative adversarial networks U-Net++ differential image Pix2Pix

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Fast and Simple Motion Tracking Unit with Motion Estimation

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Journal of Measurement Science and Instrumentation 2010年第3期1卷 233-237页

作者： Hyeon-cheol YANG Yoon-sup KIM Seong-soo LEE Sang-keun OH Sung-hwa KIM Doo-won CHOI School of Electronic Engineering Soongsil University Seoul 156- 743 Korea HyVision System Inc. Seongnam 462120 Korea

Smweillance system using active tracking camera has no distance limitation of surveillance range compared to supersonic or sound sensors. However, complex motion tracking algorithm requires huge amount of computation, and it often requires exfmasive DSPs or embedded processors. This paper proposes a novel motion tracking trait based on different image for fast and simple motion tracking. It uses configuration factor to avoid noise and inaccuracy. It reduces the required computation significantly, so as to be implemented on Field Programmable Gate Array（FFGAs ） instead of expensive Digital Signal Processing（DSPs）. It also performs calculation for motion estimation in video compression, so it can be easily combined with surveil system with video recording functionality based on video compression. The proposed motion tracking system implemented on Xilinx Vertex-4 FPGA can process 48 frames per second, and operating frequency of motion tracking trait is 100 MHz.

关键词： active tracking camera Surveillance system differential image moving picture encoding

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An Effective Method to Determine the Moving Direction of the Objects for Video Surveillance

An Effective Method to Determine the Moving Direction of the...

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2012电子信息与电气工程国际学术会议(EIEE2012)

作者： Guoqing Li Center for Space Science and Applied Research, Chinese Academy of Sciences CSSAR Graduate University of Chinese Academy of Sciences, GUCAS Bo Liu Center for Space Science and Applied Research, Chinese Academy of Sciences CSSAR Beijing, China Xiujie Jiang Center for Space Science and Applied Research, Chinese Academy of Sciences CSSAR Beijing, China

Motion detection plays an important role in video surveillance system. The sign distribution features will be covered up by the use of the absolute differential image. In this article, a method to determine the motion direction of moving objects by using the sign distribution features in the differential image of two consecutive frames is proposed. The proposed method is much lower in computational complexity than the method for calculating the motion vectors and better than the method based on more than three consecutive frames for real-time video surveillance system. Experimental results show that algorithm of the method is suitable for computer processing.

关键词： motion direction video surveillance differential image signs distribution

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