Surveillance Video Transmission Research Articles

Aka-Net: anchor free-based object detection network for surveillance video transmission in the IOT edge computing environment

Aka-Net: anchor free-based object detection network for surveillance video transmission in the IOT edge computing environment

Covert Surveillance Video Transmission with QAM Constellations Modulation

This study explores the covert transmission of surveillance videos using QAM (quadrature amplitude modulation) constellations. By analyzing transmission strategies used in surveillance video systems, we adopt KL divergence as the constraint for covertness performance and mutual information to characterize transmission rates. Utilizing the Taylor series expansion method, we simplify the complex integral calculations of mutual information and KL divergence into summation operations. This simplification not only reduces computational complexity but also ensures precise calculations. Theoretical derivations establish the necessary conditions for the covert transmission of surveillance videos, optimizing modulation probabilities for constellation points. Experimental results and simulation validations demonstrate the superior performance of our proposed method in terms of both information transfer and precision.

A compression and transmission method for surveillance video data using SPICE protocol and DWT in cloud desktop environment

In order to solve the problem that the transmission of surveillance video in cloud desktop environment will take up a large amount of network bandwidth, and the video data compression and transmission decompression program is complex, the picture quality is blurred, and the effect of SPICE accessing virtual machine is poor under the conditions of wireless and external network, a method of surveillance video data compression and transmission using SPICE protocol in cloud desktop environment is proposed. Firstly, the overall architecture of cloud desktop system is designed based on SPICE desktop virtual framework. Then, the MJPEG algorithm is used to compress the data, and the discrete wavelet transform is used to transmit the data, which will reduce the bandwidth of video data transmission and improve the transmission efficiency. Finally, the video frame is coded and transmitted by the client. The qemu-kvm server receives the coded data, decodes and restores it to the original frame, and then processes it at the back end. The experimental results show that the data compressed can greatly improve the transmission efficiency and the anti-jamming ability of video transmission, achieve the goal of accurate and efficient design, and further enhance the user’s overall experience of accessing virtual machines through SPICE.

Joint Coding-Transmission Optimization for a Video Surveillance System With Multiple Cameras

Surveillance video has become an important multi-media application in recent years, with development trends toward wide viewing angles and high definition. At the same time, transmission of surveillance video over the Internet and storage in the cloud are becoming increasingly popular. However, it is extremely challenging to transfer surveillance video with both a wide viewing angle and a high resolution over the Internet because of 1) the tradeoff between a wide viewing angle and high-surveillance object resolution for a single camera, 2) the large throughput requirement, and 3) the fluctuating delay and bandwidth of the Internet. In this paper, we present a reference-frame-cache-based surveillance video transmission system (RSVTS), which delivers wide-viewing-angle and high-definition surveillance video over the Internet in real time using multiple rotatable cameras. First, we develop an efficient video mosaicing method for merging two (or more) surveillance videos together. Second, novel reference frame selection and update algorithms are proposed for the RSVTS encoder to reduce the amount of encoded data. Third, we implement a reference frame cache on both the sender and receiver sides to increase video quality by increasing the probability of video decoding. We conduct a performance evaluation using a simulation system that integrates RSVTS and ns-3. Compared with the H.264/SVC and H.264/AVC schemes, RSVTS achieves appreciable improvements in enhancing the video peak signal-to-noise ratio and bandwidth conservation.

Error-resilient surveillance video transmission based on a practical joint source-channel distortion computing model

In recent years, IP (Internet Protocol)-based video surveillance has widely been useful for post-event analysis and assisting the work of privacy protection and public safety. To support high-quality IP video surveillance, error-resilience techniques are important for surveillance system design, because video has more stringent requirements than general video transmission for packet loss, latency, and jitter. The optimal FEC (forward error correction) code rate decision is a crucial procedure to determine the optimal source and channel coding rates to minimize the overall picture distortion when transporting video packets over packet loss channels. The conventional FEC code rate decision schemes using an analytical source-coding distortion model and a channel-induced distortion model are usually complex and typically employ the process of model parameter training, which involves potentially high computational complexity and implementation cost. To avoid the complex modeling procedure, we propose a simple but accurate joint source-channel distortion model to estimate the channel-loss threshold set for optimal FEC code rate decision. Since the proposed model is expressed as a simple closed form and has a small number of scene-dependent model parameters, a video sender of the surveillance system using the model can be easily implemented. For training the scene-dependent model parameters in real time, we propose a practical test-run procedure. This method accelerates the test-run while maintaining its accuracy for training the scene-dependent model parameters. Using the proposed simple model and practical test-run method, the video sender can find the optimal code rate for on-the-fly joint source-channel coding whenever there is a change in the packet-loss condition in the channel. Simulations show that the proposed method can accurately estimate the channel loss threshold set, resulting in an optimal FEC code rate with low computational complexity.