Modeling and Optimization of Bandwidth Supply Performance for Cloud-Assisted Video Systems under Flash Crowd

The large-scale and sudden video content access such as flash crowds results in huge bandwidth demand,which severely influence user quality of experience and quality of service of video systems.In this paper,we firstly discuss the main reason of generation of flash crowds for video streaming services and analyze key factor for balance recovery between supply and demand of upload bandwidth.We construct two models:bandwidth supply capacity model of video systems and bandwidth demand model of users,which measures usage amount of bandwidth of the cloud.Based on the built models,we further employ a community-based cooperative caching strategy of video resources to promote supply capacity of upload bandwidth of video systems.Extensive tests show how the proposed cooperative caching strategy achieves much better performance results in comparison with original solution.

MULTI-EPIPOLAR LINES MATCHING-BASED RAY-SPACE INTERPOLATION FOR FREE VIEWPOINT VIDEO SYSTEM

Ray-space based arbitrary viewpoint rendering without complex object segmentation or model construction is the main technology to realize Free Viewpoint Video(FVV) system for complex scenes. Ray-space interpolation and compression are two key techniques for the solution. In this paper,correlation among multiple epipolar lines in ray-space data is analyzed,and a new method of ray-space interpolation with multi-epipolar lines matching is proposed. Comparing with the pixel-based matching interpolation method and the block-based matching interpolation method,the proposed method can achieve higher Peak Signal to Noise Ratio(PSNR) in interpolating rayspace data and rendering arbitrary viewpoint images.

Video Recommendation System Using Machine-Learning Techniques

In the realm of contemporary artificial intelligence,machine learning enables automation,allowing systems to naturally acquire and enhance their capabilities through learning.In this cycle,Video recommendation is finished by utilizing machine learning strategies.A suggestion framework is an interaction of data sifting framework,which is utilized to foresee the“rating”or“inclination”given by the different clients.The expectation depends on past evaluations,history,interest,IMDB rating,and so on.This can be carried out by utilizing collective and substance-based separating approaches which utilize the data given by the different clients,examine them,and afterward suggest the video that suits the client at that specific time.The required datasets for the video are taken from Grouplens.This recommender framework is executed by utilizing Python Programming Language.For building this video recommender framework,two calculations are utilized,for example,K-implies Clustering and KNN grouping.K-implies is one of the unaided AI calculations and the fundamental goal is to bunch comparable sort of information focuses together and discover the examples.For that K-implies searches for a steady‘k'of bunches in a dataset.A group is an assortment of information focuses collected due to specific similitudes.K-Nearest Neighbor is an administered learning calculation utilized for characterization,with the given information;KNN can group new information by examination of the‘k'number of the closest information focuses.The last qualities acquired are through bunching qualities and root mean squared mistake,by using this algorithm we can recommend videos more appropriately based on user previous records and ratings.

Real-time moving object detection for video monitoring systems

Moving object detection is one of the challenging problems in video monitoring systems, especially when the illumination changes and shadow exists. Amethod for real-time moving object detection is described. Anew background model is proposed to handle the illumination varition problem. With optical flow technology and background subtraction, a moving object is extracted quickly and accurately. An effective shadow elimination algorithm based on color features is used to refine the moving obj ects. Experimental results demonstrate that the proposed method can update the background exactly and quickly along with the varition of illumination, and the shadow can be eliminated effectively. The proposed algorithm is a real-time one which the foundation for further object recognition and understanding of video mum＇toting systems.

Design and implementation of multi-hop video transmission experiment system in VANET

Abts ract A wireless mutl i-hop videot ransmission experiment system is designed and implemented for vehiculra ad-hoc networks VANET and the rt ansm ission control protocol and routing protocol are proposed. This system in tegrates the embedded Linux system witha n ARM kernel and oc ns ists of a S3C6410 main control module a wirel ss local arean etwork WLAN card a LCD screne and so on.In the scenario of a wireless multi-hop video transmission both the H.264 and JPEG are used and their performances such as the compression rate delay and frame loss rate are analyzed in theory andc ompared in the experiment.The system is tested in the real indoor and outdoor environment.The results show that the scheme of the multi-hop video transmission experiment system can be applicable for VANET and multiple scenes and the transmission control protocol and routing protocol proposed can achieve real-time transmission and meet multi-hop requirements.

Video Based Vehicle Detection and its Application in Intelligent Transportation Systems

Video based vehicle detection technology is an integral part of Intelligent Transportation System (ITS), due to its non-intrusiveness and comprehensive vehicle behavior data collection capabilities. This paper proposes an efficient video based vehicle detection system based on Harris-Stephen corner detector algorithm. The algorithm was used to develop a stand alone vehicle detection and tracking system that determines vehicle counts and speeds at arterial roadways and freeways. The proposed video based vehicle detection system was developed to eliminate the need of complex calibration, robustness to contrasts variations, and better performance with low resolutions videos. The algorithm performance for accuracy in vehicle counts and speed was evaluated. The performance of the proposed system is equivalent or better compared to a commercial vehicle detection system. Using the developed vehicle detection and tracking system an advance warning intelligent transportation system was designed and implemented to alert commuters in advance of speed reductions and congestions at work zones and special events. The effectiveness of the advance warning system was evaluated and the impact discussed.

FPGA BASED REAL-TIME VIDEO IMAGE ACQUISITION AND STORAGE SYSTEM

To overcome the traditional disadvantages, an improved FPGA-core based real-time video image acqui- sition and storage system is designed. The modular designed by Verilog programming is used for video decoding of A/D configuration, video image capturing logic control and image storage logic control modules. And IDE in- terface bard disk as storage medium and FAT32 file system as record form are used for real-time image storage. Experimental results show that the system has the advantages of strong real-time capability, high integration, powerful storage, easy expansibility and so on.

Video Based Fire Detection Systems on Forest and Wildland Using Convolutional Neural Network

The devastating effects of wildland fire are an unsolved problem,resulting in human losses and the destruction of natural and economic resources.Convolutional neural network(CNN)is shown to perform very well in the area of object classification.This network has the ability to perform feature extraction and classification within the same architecture.In this paper,we propose a CNN for identifying fire in videos.A deep domain based method for video fire detection is proposed to extract a powerful feature representation of fire.Testing on real video sequences,the proposed approach achieves better classification performance as some of relevant conventional video based fire detection methods and indicates that using CNN to detect fire in videos is efficient.To balance the efficiency and accuracy,the model is fine-tuned considering the nature of the target problem and fire data.Experimental results on benchmark fire datasets reveal the effectiveness of the proposed framework and validate its suitability for fire detection in closed-circuit television surveillance systems compared to state-of-the-art methods.

Joint resource allocation for MIMO-OFDM video transmission systems with unequal error protection

To improve the performance of MIMO-OFDM video transmission systems on the limitation of wireless bandwidth and transmitting power,we propose an adaptive joint resource allocation algorithm with unequal error protection(UEP) based on joint source-channel coding(JSCC) according to H.264 video compression standard and RCPT channel coding.According to different thresholds of the average SNR of subchannels,the algorithm dynamically allocates the source coding parameters of original video data and the channel coding parameters of RCPT,which realizes UEP for the compressed video data of different importance.Through the bit and power allocation based on MQAM modulation and the subspace allocation based on beamforming technology for different subcarriers,an adaptive joint resource allocation making full use of space-frequency domain resources have been realized.The simulation results indicate that the algorithm improves the adaptability of video transmission systems in different wireless environments and the quality of video retrieval.

Video Scene Invariant Crowd Density Estimation Using Geographic Information Systems

Crowd density is an important factor of crowd stability.Previous crowd density estimation methods are highly dependent on the specific video scene.This paper presented a video scene invariant crowd density estimation method using Geographic Information Systems(GIS) to monitor crowd size for large areas.The proposed method mapped crowd images to GIS.Then we can estimate crowd density for each camera in GIS using an estimation model obtained by one camera.Test results show that one model obtained by one camera in GIS can be adaptively applied to other cameras in outdoor video scenes.A real-time monitoring system for crowd size in large areas based on scene invariant model has been successfully used in 'Jiangsu Qinhuai Lantern Festival,2012'.It can provide early warning information and scientific basis for safety and security decision making.

Interactive System for Video Summarization Based on Multimodal Fusion

Biography videos based on life performances of prominent figures in history aim to describe great mens' life.In this paper,a novel interactive video summarization for biography video based on multimodal fusion is proposed,which is a novel approach of visualizing the specific features for biography video and interacting with video content by taking advantage of the ability of multimodality.In general,a story of movie progresses by dialogues of characters and the subtitles are produced with the basis on the dialogues which contains all the information related to the movie.In this paper,JGibbsLDA is applied to extract key words from subtitles because the biography video consists of different aspects to depict the characters' whole life.In terms of fusing keywords and key-frames,affinity propagation is adopted to calculate the similarity between each key-frame cluster and keywords.Through the method mentioned above,a video summarization is presented based on multimodal fusion which describes video content more completely.In order to reduce the time spent on searching the interest video content and get the relationship between main characters,a kind of map is adopted to visualize video content and interact with video summarization.An experiment is conducted to evaluate video summarization and the results demonstrate that this system can formally facilitate the exploration of video content while improving interaction and finding events of interest efficiently.

Suitability of VVC and HEVC for Video Telehealth Systems

Video compression in medical video streaming is one of the key technologies associated with mobile healthcare.Seamless delivery of medical video streams over a resource constrained network emphasizes the need of a video codec that requires minimum bitrates and maintains high perceptual quality.This paper presents a comparative study between High Efciency Video Coding(HEVC)and its potential successor Versatile Video Coding(VVC)in the context of healthcare.A large-scale subjective experiment comprising of twenty-four non-expert participants is presented for eight different test conditions in Full High Denition(FHD)videos.The presented analysis highlights the impact of compression artefacts on the perceptual quality of HEVC and VVC processed videos.Our results and ndings show that VVC clearly outperforms HEVC in terms of achieving higher compression,while maintaining high quality in FHD videos.VVC requires upto 40%less bitrate for encoding an FHD video at excellent perceptual quality.We have provided rate-quality curves for both encoders and a degree of overlap across both codecs in terms of perceptual quality.Overall,there is a 71%degree of overlap in terms of quality between VVC and HEVC compressed videos for eight different test conditions.

Research on Remote Video Monitoring System Used for Numerical Control Machine Tools Based on Embedded Technology

This paper designed an embedded video monitoring system using DSP (Digital Signal Processing ) and ARM (Ad- vanced RISC Machine).This system is an important part of self-service operation of numerical control machine tools,At first the analog input signals from the CCD(Charge Coupled Device) camera are transformed into digital signals,and then output to the DSP system,where the video sequence is encoded according to the new generation image compressing standard called H.264.The code will be transmitted to the ARM system through xBus,and then be packed in the ARM system and transmitted to the client port through the gateway.Web technology,embedded technology and image compressing as well as coding technology are integrated in the system,which can be widely used in self-service operation of numerical control machine tools and intelligent robot control areas.

Real-time Audio &Video Transmission System Based on Visible Light Communication

With the increasing popularity of solid sate lighting devices, Visible Light Communication (VLC) is globally recognized as an advanced and promising technology to realize short-range, high speed as well as large capacity wireless data transmission. In this paper, we propose a prototype of real-time audio and video broadcast system using inexpensive commercially available light emitting diode (LED) lamps. Experimental results show that real-time high quality audio and video with the maximum distance of 3 m can be achieved through proper layout of LED sources and improvement of concentration effects. Lighting model within room environment is designed and simulated which indicates close relationship between layout of light sources and distribution of illuminance.

Reversible Video Steganography Using Quick Response Codes and Modified ElGamal Cryptosystem

The rapid transmission of multimedia information has been achieved mainly by recent advancements in the Internet’s speed and information technology.In spite of this,advancements in technology have resulted in breaches of privacy and data security.When it comes to protecting private information in today’s Internet era,digital steganography is vital.Many academics are interested in digital video because it has a great capability for concealing important data.There have been a vast number of video steganography solutions developed lately to guard against the theft of confidential data.The visual imperceptibility,robustness,and embedding capacity of these approaches are all challenges that must be addressed.In this paper,a novel solution to reversible video steganography based on Discrete Wavelet Transform(DWT)and Quick Response(QR)codes is proposed to address these concerns.In order to increase the security level of the suggested method,an enhanced ElGamal cryptosystem has also been proposed.Prior to the embedding stage,the suggested method uses the modified ElGamal algorithm to encrypt secret QR codes.Concurrently,it applies two-dimensional DWT on the Y-component of each video frame resulting in Approximation(LL),Horizontal(LH),Vertical(HL),and Diagonal(HH)sub-bands.Then,the encrypted Low(L),Medium(M),Quantile(Q),and High(H)QR codes are embedded into the HL sub-band,HHsub-band,U-component,and V-component of video frames,respectively,using the Least Significant Bit(LSB)technique.As a consequence of extensive testing of the approach,it was shown to be very secure and highly invisible,as well as highly resistant to attacks from Salt&Pepper,Gaussian,Poisson,and Speckle noises,which has an average Structural Similarity Index(SSIM)of more than 0.91.Aside from visual imperceptibility,the suggested method exceeds current methods in terms of Peak Signal-to-Noise Ratio(PSNR)average of 52.143 dB,and embedding capacity 1 bpp.

Robotic single-incision left hemihepatectomy for intrahepatic bile duct stones by Da Vinci single-site surgical system: A case report with video

Minimally invasive surgery is a trend in hepatobiliary surgery.A 56-year-old female patient was admitted to our institution for intrahepatic lithiasis.The CT scan showed multiple calculi in the left liver,dilation of the left intrahepatic bile duct and liver atrophy of the left lobe.Robotic single-incision left hemihepatectomy by the single-site systemwas successfully applied.With the idea of enhanced recovery after surgery,the patient was discharged on the third day after the operation without any morbidity.Robotic single-incision surgery is more frequent in gynecologic and urological surgery.As far as we know,this is the first robotic single-incision left hemihepatectomy report in the world.

Design and Implementation of GIS Data Production System for Expressway Video and Road Infostructure

The expressway is necessary for the development of the modern transportation industry, and the level of expressway construction reflects the overall grade of national or regional economic development. In order to process the expressway road property data information, based on the current mainstream Windows operating system, this study utilizes Geographic Information System (GIS) development technology, road video processing technology, and spatial data mining method to design and develop an expressway video and road infostructure GIS data production system. The system designs a multi-layer distributed application model in accordance with the ideas and methods of GIS engineering and the characteristics of road production data. In addition, according to the characteristics and specification requirements of basic geographic data, the road production database of spatial data and attribute data integrated storage is constructed by combining database and spatial data engine. Through the development of the GIS data production system for expressway video and road infostructure, various functions such as generation of road property data, dynamic management of road infostructure, and visualization of spatial information have been realized. The system focuses on improving the production efficiency and automation level of expressway production data and meets the construction requirements for modernization, informatization, and intelligence of expressways.

THE APPLICATION RESEARCH OF VIDEO SERVER SYSTEM FOR VIDEO ON DEMAND

A comprehensive research on key issues of the large-scale video server system for Video On Demand (VOD) client/server system is conducted based mainly on real time (rt)/non-real time (nrt) Variable Bit Rate or Constant Bit Rate (VBR/CBR) MPEG-2 MP@ML Signal Program Transport Stream (SPTS) for movies, and general architecture for storage, control, caching subsystems from Loosely Coupled Computer (LCC), Symmetric Multiple Processing (SMP), and Massively Parallel Processing (MPP) video server is conceptualized. Meanwhile, Redundant Array of Inexpensive Disks (RAID) storage system are presented and the centralized FCP/SAN huge storage technology is introduced in terms of its scalability, throughput, and connectivity performances.

Realtime Object Detection Through M-ResNet in Video Surveillance System

Object detection plays a vital role in the video surveillance systems.To enhance security,surveillance cameras are now installed in public areas such as traffic signals,roadways,retail malls,train stations,and banks.However,monitor-ing the video continually at a quicker pace is a challenging job.As a consequence,security cameras are useless and need human monitoring.The primary difficulty with video surveillance is identifying abnormalities such as thefts,accidents,crimes,or other unlawful actions.The anomalous action does not occur at a high-er rate than usual occurrences.To detect the object in a video,first we analyze the images pixel by pixel.In digital image processing,segmentation is the process of segregating the individual image parts into pixels.The performance of segmenta-tion is affected by irregular illumination and/or low illumination.These factors highly affect the real-time object detection process in the video surveillance sys-tem.In this paper,a modified ResNet model(M-Resnet)is proposed to enhance the image which is affected by insufficient light.Experimental results provide the comparison of existing method output and modification architecture of the ResNet model shows the considerable amount improvement in detection objects in the video stream.The proposed model shows better results in the metrics like preci-sion,recall,pixel accuracy,etc.,andfinds a reasonable improvement in the object detection.

Video-assisted bystander cardiopulmonary resuscitation improves the quality of chest compressions during simulated cardiac arrests: A systemic review and meta-analysis

BACKGROUND It remains unclear whether video aids can improve the quality of bystander cardiopulmonary resuscitation(CPR).AIM To summarize simulation-based studies aiming at improving bystander CPR associated with the quality of chest compression and time-related quality parameters.METHODS The systematic review was conducted according to the PRISMA guidelines.All relevant studies were searched through PubMed,EMBASE,Medline and Cochrane Library databases.The risk of bias was evaluated using the Cochrane collaboration tool.RESULTS A total of 259 studies were eligible for inclusion,and 6 randomised controlled trial studies were ultimately included.The results of meta-analysis indicated that video-assisted CPR(V-CPR)was significantly associated with the improved mean chest compression rate[OR=0.66(0.49-0.82),P<0.001],and the proportion of chest compression with correct hand positioning[OR=1.63(0.71-2.55),P<0.001].However,the difference in mean chest compression depth was not statistically significant[OR=0.18(-0.07-0.42),P=0.15],and V-CPR was not associated with the time to first chest compression compared to telecommunicator CPR[OR=-0.12(-0.88-0.63),P=0.75].CONCLUSION Video real-time guidance by the dispatcher can improve the quality of bystander CPR to a certain extent.However,the quality is still not ideal,and there is a lack of guidance caused by poor video signal or inadequate interaction.