Smart all-time vision:The battery-free video communication for urban administration and law enforcement

The Chinese government is dedicated to enhancing the level of informatization in administrative law enforcement to ensure fairness and increase credibility.Currently,law enforcement has exposed such problems as insufficient force,difficulties in collecting evidence,and low evidential power.These problems contradict the principles of rule of law and standardization.Many local governments have implemented advanced information technologies for urban administration and law enforcement,including big data,artificial intelligence,and IoT.Among these technologies,IoT is the core communication infrastructure for innovative law enforcement platforms.However,traditional video communications rely on batteries or dedicated power sources,leading to maintenance challenges and high power consumption.In this paper,we propose AT-Eye,a new video communication paradigm for all-time law enforcement video monitoring,which is battery-free and high-throughput.The key enabler of AT-Eye is ambient backscatter technology,which enables energy harvesting and video communication simultaneously.Unlike previous methods,our proposal introduces a novel CCK-based modulation for tag cameras and achieves 4-way concurrency.The modulation is simple because it uses phase difference and it is energyefficient because generating square waves is adequate.Moreover,to ensure full compatibility with COTS WiFi,we modulate the physical service data unit.Therefore,data recovery is possible using only commercial NICs.We conduct comprehensive experiments to examine our proposal and experiment results show that AT-Eye achieves a throughput of 10.8 Mbps with COTS radios.We also simulate a 16-way battery-free tag camera system,demonstrating AT-Eye’s feasibility of high-definition video communication.

Multi-radio access based bandwidth allocation strategy for video communication in heterogeneous wireless networks

In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.

Cloud-based video communication and networking: an architectural overview

Cloud-based video communication and networking has emerged as a promising new research paradigm to significantly improve the quality of experience for video consumers.An architectural overview of this promising research area was presented.This overview with an end-to-end partition of the cloud-based video system into major blocks with respect to their locations from the center of the cloud to the edge of the cloud was started.Following this partition,existing research efforts on how the principles of cloud computing can provide unprecedented support to 1)video servers,2)content delivery networks,and 3)edge networks within the global cloud video ecosystems were examined.Moreover,a case study was exemplfied on an edge cloud assisted HTTP adaptive video streaming to demonstrate the effectiveness of cloud computing support.Finally,by envisioning a list of future research topics in cloud-based video communication and networking a coclusion is made.

Optimal video communication strategy for intelligent video analysis in unmanned aerial vehicle applications

For Unmanned Aerial Vehicles(UAV),the intelligent video analysis is a key technology in intelligent autonomous control,real-time navigation and surveillance.However,poor UAV wireless links would degrade the quality of video communication,leading to difficulties in video analysis.To meet the challenges of packet-loss and limited bandwidth in adverse UAV channel environments,this paper proposes a parameter optimization mechanism for UAV intelligent video analysis.In the proposed method,an Optimal Strategy Library(OSL)is designed to optimize the parameters for video encoding and forward error correction.Adapted to the packet-loss rate and bandwidth in practical UAV wireless network,the proposed OSL can facilitate the encoding of video sequences and the recovery of degraded videos with optimal performance.Experimental results demonstrate that the proposed solution can keep intelligent video analysis working efficiently with adverse UAV wireless links,and is capable of maximizing the inference accuracy of Multi-Object Tracking(MOT)algorithms in various scenarios.

H.263 VIDEO CODEC IMPLEMENTATION BASED ON MULTIMEDIA DSP

This letter introduces the implementation of H.263 video codec based on multimedia DSP TM1300, and discuses several key problems related to video coding.

ESSENTIAL INFORMATION AGGREGATION OF INTRA CODED VIDEO FRAME FOR WIRELESS TRANSMISSON

A novel error resilient method based on Essential Information Aggregation (EIA) technique is proposed for robust wireless transmission of intra coded video frames. This method modifies the original video stream structure so as to mitigate the effect of decoding loss of synchronization within a video frame, for which Macro Block Aligned (MBA) error detection method is accompanied to be developed. Experiments on an Additive White Gaussian Noise (AWGN) wireless simulation platform and H.263+ baseline video codec show that it can obtain better subjective and objective image quality than existing error resilience approaches.

Improving Low Bitrate Video Coding via Computation Incorporating A Priori Information

The growing number of mobile users, as well as the diversification in types of services have resulted in increasing demands for wireless network bandwidth in recent years. Although evolving transmission techniques are able to enlarge the network capacity to some degree, they still cannot satisfy the requirements of mobile users. Meanwhile, following Moore's Law, the data processing capabilities of mobile user terminals are continuously improving. In this paper, we explore possible methods of trading strong computational power at wireless terminals for transmission efficiency of communications. Taking the specific scenario of wireless video conversation, we propose a model-based video coding scheme by learning the structures in multimedia contents. Benefiting from both strong computing capability and pre-learned model priors, only low-dimensional parameters need to be transmitted; and the intact multimedia contents can also be reconstructed at the receivers in real-time. Experiment results indicate that, compared to conventional video codecs, the proposed scheme significantly reduces the data rate with the aid of computational capability at wireless terminals.

SPATIAL ERROR CONCEALMENT BASED ON MOJETTE TRANSFORM

This letter presents a novel spatial error concealment algorithm for the H.264 video coding. The error concealment algorithm is based on directional interpolation. Mojette transform is used to estimate the orientation features of the damaged blocks,and the image is interpolated in the appro-priate directions. The proposed method is compared with bilinear interpolation algorithm in the ref-erence implementation of H.264 and all directional interpolation. Experimental results prove that the proposed algorithm has better subjective and objective image reconstruction quality.

Optimization-Based Fragmental Transmission Method for Video Data in Opportunistic Networks

Multimedia data have become popularly transmitted content in opportunistic networks. A large amount of video data easily leads to a low delivery ratio. Breaking up these big data into small pieces or fragments is a reasonable option. The size of the fragments is critical to transmission efficiency and should be adaptable to the communication capability of a network. We propose a novel communication capacity calculation model of opportunistic network based on the classical random direction mobile model, define the restrain facts model of overhead, and present an optimal fragment size algorithm. We also design and evaluate the methods and algorithms with video data fragments disseminated in a simulated environment. Experiment results verified the effectiveness of the network capability and the optimal fragment methods.