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Intelligent Express Delivery System Based on video processing

2011 International Conference on Fuzzy Systems and Neural Computing(FSNC 2011)

作者： Lei Zhang Da Li Xinxiang University School of Information Engineering WUHAN University of Technology School of Electronics and Information Engineering Xi'an Jiao tong University

The MPSo C system is the promising solution for the coming complex embedded system of high *** this paper studied the real-time dynamic scheduling with inaccurate and uncertain characteristics on MPSo C *** authors propose a new dynamic fuzzy heuristic scheduling to solve the scheduling problem and improve the multiple *** this MPSo C Architecture has been implemented as a prototype MPSo C system on FPGA,which utilizes the proposed fuzzy dynamic scheduling algorithm to allocating tasks onto the *** in our case studies,we design a parallel architecture h.264 encoder,running on a multicore MPSo C system on *** speedup ratio of this prototype application system is up to 12.69.

关键词： MPSo C System Dynamic Scheduling Fuzzy Set video processing Parallel processing

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国际计算机前沿大会会议论文集 2021年第1期 370-379页

作者： Chuang Xu Yanqing Wang Ruyu Sheng Wenjun Lu College of Information Engineering Nanjing Xiaozhuang UniversityNanjing 211171China

Although the scale of the express industry is large, it is difficult toachieve the function of fully intelligent receiving and sending express. In thispaper, the intelligent express delivery system is proposed based on the imageand video processing technology of OpenCV, the Faster R-CNN object detectionalgorithm and other technologies. Through the depth camera and electronic scale,it can identify the object category, volume and weight of the items placed on thescale by the sender and store the video of the objects packed into the cabinet. Theoverall framework of the systemwas constructed;key technologies were applied torealize the system;the function of the system was tested. The experimental resultsshow that it achieves the intelligent automation of delivery and delivery throughthe integrated express delivery system of intelligent identification and informationtraceability, which promotes the development of express delivery industry.

关键词： video processing Object recognition Intelligent express delivery system

Static Scene Illumination Estimation from videos with Applications

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Journal of Computer Science & Technology 2017年第3期32卷 430-442页

作者： Bin Liu Nun Xu Ralph R. Martin Department of Computer Science and Technology Tsinghua University Beijing 100084 China School of Computer Science and Informatics Cardiff University Cardiff CF243AA U.K.

We present a system that automatically recovers scene geometry and illumination from a video, providing a basis for various applications. Previous image based illumination estimation methods require either user interaction or external information in the form of a database. We adopt structure-from-motion and multi-view stereo for initial scene reconstruction, and then estimate an environment map represented by spherical harmonics （as these perform better than other bases）. We also demonstrate several video editing applications that exploit the recovered geometry and illumination, including object insertion （e.g., for augmented reality）, shadow detection, and video relighting.

关键词： video processing augmented reality illumination recovery

Visual-attention gabor filter based online multi-armored target tracking

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Defence Technology（防务技术） 2021年第4期17卷 1249-1261页

作者： Fan-jie Meng Xin-qing Wang Fa-ming Shao Dong Wang Yao-wei Yu Yi Xiao Department of Mechanical Engineering College of Field EngineeringArmy Engineering University of PLANanjing 210007China College of Civil Aviation Nanjing University of Aeronautics and AstronauticsNanjing 210007China

The multi-armored target tracking(MATT)plays a crucial role in coordinated tracking and *** occlusion and insertion among targets and target scale variation is the key problems in *** stateof-the-art multi-object tracking(MOT)works adopt the tracking-by-detection strategy,which rely on compute-intensive sliding window or anchoring scheme in detection module and neglect the target scale variation in tracking *** this work,we proposed a more efficient and effective spatial-temporal attention scheme to track multi-armored target in the ground *** simulating the structure of the retina,a novel visual-attention Gabor filter branch is proposed to enhance *** introducing temporal information,some online learned target-specific Convolutional Neural Networks(CNNs)are adopted to address *** importantly,we built a MOT dataset for armored targets,called Armored Target Tracking dataset(ATTD),based on which several comparable experiments with state-ofthe-art methods are *** results show that the proposed method achieves outstanding tracking performance and meets the actual application requirements.

关键词： Multi-object tracking Deep learning Gabor filter Biological vision Military Application video processing

Dance to the beat： Synchronizing motion to audio

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Computational Visual Media 2018年第3期4卷 197-208页

作者： Rachele Bellini Yanir Kleimani Daniel Cohen-Or Tel Aviv University Tel Aviv 6997801 Israel.

In this paper we introduce a video post-processing method that enhances the rhythm of a dancing performance,in the sense that the dancing movements are more in time to the beat of the *** dancing performance as observed in a video is analyzed and segmented into motion intervals delimited by motion *** present an image-space method to extract the motion beats of a video by detecting frames at which there is a significant change in direction or motion *** motion beats are then synchronized with the music beats such that as many beats as possible are matched with as little as possible time-warping distortion to the *** show two applications for this cross-media synchronization:one where a given dance performance is enhanced to be better synchronized with its original music,and one where a given dance video is automatically adapted to be synchronized with different music.

关键词： video processing synchronization motionsegmentation video analysis

Deeply‐Recursive Attention Network for video steganography

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1507-1523页

作者： Jiabao Cui Liangli Zheng Yunlong Yu Yining Lin Huajian Ni Xin Xu Zhongfei Zhang College of Computer Science and Technology Zhejiang UniversityHangzhouChina School of Software Technology Zhejiang UniversityNingboChina College of Information Science and Electronic Engineering Zhejiang UniversityHangzhouChina Shanghai SUPREMIND Technology Co. Ltd.ShanghaiChina College of Intelligence Science and Technology National University of Defense TechnologyChangshaChina Department of Computer Science Binghamton UniversityBinghamtonNew YorkUSA

video steganography plays an important role in secret communication that conceals a secret video in a cover video by perturbing the value of pixels in the cover *** is the first and foremost requirement of any steganographic *** by the fact that human eyes perceive pixel perturbation differently in different video areas,a novel effective and efficient Deeply‐Recursive Attention Network(DRANet)for video steganography to find suitable areas for information hiding via modelling spatio‐temporal attention is *** DRANet mainly contains two important components,a Non‐Local Self‐Attention(NLSA)block and a Non‐Local Co‐Attention(NLCA)***,the NLSA block can select the cover frame areas which are suitable for hiding by computing the correlations among inter‐and intra‐cover *** NLCA block aims to effectively produce the enhanced representations of the secret frames to enhance the robustness of the model and alleviate the influence of different areas in the secret ***,the DRANet reduces the model parameters by performing similar operations on the different frames within an input video *** results show the proposed DRANet achieves better performance with fewer parameters than the state‐of‐the‐art competitors.

关键词： data privacy video processing

Sparse Crowd Flow Analysis of Tawaaf of Kaaba During the COVID-19 Pandemic

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Computers, Materials & Continua 2022年第6期71卷 5581-5601页

作者： Durr-e-Nayab Ali Mustafa Qamar Rehan Ullah Khan Waleed Albattah Khalil Khan Shabana Habib Muhammad Islam Department of Computer Systems Engineering University of Engineering and TechnologyPeshawarPakistan Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Technology and Computer Science Pak-Austria FachhochschuleInstitute of Applied Sciences and TechnologyHaripurPakistan Department of Electrical Engineering College of Engineering and Information TechnologyOnaizah CollegesAl-QassimSaudi Arabia

The advent of the COVID-19 pandemic has adversely affected the entire world and has put forth high demand for techniques that remotely manage crowd-related *** surveillance and crowd management using video analysis techniques have significantly impacted today’s research,and numerous applications have been developed in this *** research proposed an anomaly detection technique applied to Umrah videos in Kaaba during the COVID-19 pandemic through sparse crowd *** theKaaba rituals is crucial since the crowd gathers from around the world and requires proper analysis during these days of the *** Umrah videos are analyzed,and a system is devised that can track and monitor the crowd flow in *** crowd in these videos is sparse due to the pandemic,and we have developed a technique to track the maximum crowd flow and detect any object(person)moving in the direction unlikely of the major *** have detected abnormal movement by creating the histograms for the vertical and horizontal flows and applying thresholds to identify the non-majority *** algorithm aims to analyze the crowd through video surveillance and timely detect any abnormal activity tomaintain a smooth crowd flowinKaaba during the pandemic.

关键词： Computer vision COVID sparse crowd crowd analysis flow analysis sparse crowd management tawaaf video analysis video processing

Multiple Forgery Detection in video Using Convolution Neural Network

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Computers, Materials & Continua 2022年第10期73卷 1347-1364页

作者： Vinay Kumar Vineet Kansal Manish Gaur Centre for Advanced Studies Dr.A P J Abdul Kalam Technical UniversityLucknowIndia Institute of Engineering and Technology Dr.A P J Abdul Kalam Technical UniversityLucknowIndia

With the growth of digital media data manipulation in today’s era due to the availability of readily handy tampering software,the authenticity of records is at high risk,especially in *** is a dire need to detect such problem and do the necessary *** this work,we propose an approach to detect the interframe video forgery utilizing the deep features obtained from the parallel deep neural network model and thorough analytical *** proposed approach only uses the deep features extracted from the CNN model and then applies the conventional mathematical approach to these features to find the forgery in the *** work calculates the correlation coefficient from the deep features of the adjacent frames rather than calculating directly from the *** divide the procedure of forgery detection into two phases–video forgery detection and video forgery *** video forgery detection,this approach detect input video is original or *** the video is not original,then the video is checked in the next phase,which is video forgery *** the video forgery classification,method review the forged video for insertion forgery,deletion forgery,and also again check for *** proposed work is generalized and it is tested on two different *** experimental results of our proposed model show that our approach can detect the forgery with the accuracy of 91%on VIFFD dataset,90%in TDTV dataset and classify the type of forgery–insertion and deletion with the accuracy of 82%on VIFFD dataset,86%on TDTV *** work can helps in the analysis of original and tempered video in various domain.

关键词： Digital forensic forgery detection video authentication video interframe forgery video processing deep learning

De-interlacing technique based on total variation with spatial-temporal smoothness constraint

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Science in China(Series F) 2007年第4期50卷 561-575页

作者： YIN XueMin1,2,3, YUAN JianHua1,2, LU XiaoPeng1,2 & ZOU MouYan1,2 1 Institute of Electronics, Chinese Academy of Sciences, Beijing 100080, China 2 Graduate School, Chinese Academy of Sciences, Beijing 100039, China 3 Jiuquan Satellite Launch Center, Lanzhou 732750, China Institute of Electronics Chinese Academy of Sciences Beijing China Graduate School Chinese Academy of Sciences Beijing China Jiuquan Satellite Launch Center Lanzhou China

This paper introduces a new method of converting interlaced video to a progressively scanned video and image, The new method is derived from Bayesian framework with the spatial-temporal smoothness constraint and the MAP is done by minimizing the energy functional, The half-quadratic regularization method is used to solve the corresponding partial differential equations （PDEs）, This approach gives the improved results over the conventional de-interlacing methods, Two criteria are proposed in the paper, and they can be used to evaluate the performance of the de-interlacing algorithms,

关键词： video processing de-interlacing total variation spatio-temporai smoothness constraint PDEs half-quadratic regularization