Sensor-Assisted Global Motion Estimation for Efficient UAV Video Coding

Mi, Yang; Luo, Chunbo; Min, Geyong; Miao, Wang; Wu, Liang; Zhao, Tianxiao

doi:10.1109/icassp.2019.8682798

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Other potential work includes the consideration of multiple modulation schemes and large-scale fading in the UAV channel model. Moreover, the performance enhancement of combining the theoretical model and algorithms at the application level, e.g., adaptive video compression [41], will also be examined in our future works.…”

Section: Discussionmentioning

confidence: 99%

Enabling Capacity Estimation With Ergodic Interference Power in Cellular-Based Multiple UAV Systems

Zhao

Zhou

et al. 2020

IEEE Access

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The integration of unmanned aerial vehicles (UAVs) into cellular networks as aerial user equipment (aUE) has attracted increasing interest from both academia and industry in recent years. To ensure stable uplink (UL) service performance, the potential UL capacity must be determined for a variety of communication techniques to guide the system design or to obtain an optimized solution. Unlike traditional interferences from ground UEs, which contribute to only local and nearby cells, UAV systems involve strong LoS paths to even far side base stations (BSs) due to higher altitude. As a result, intercell interference becomes the dominating factor in the estimation of the potential capacity. In this paper, we propose a theoretical model on the ergodic sum power of the interference arising from all UAVs maintaining LoS paths with the target BS. The solution to this model is difficult to obtain, and is essentially rooted in the dynamic trajectories of interfering UAVs within a vast geological range. To address this problem, we divide the model into noncorrelated parts, where each part contains the interfering UAVs that are independently and identically distributed (i.i.d.). Then we utilize the ergodic method to solve the interference power of each part. Based on this, the original nonanalytical expression for the ergodic sum interference power is transformed into a solvable integration problem, and the closed-form solution is successfully derived. Simulation based experiments are conducted on both rural macro (RMa) cell and urban macro (UMa) cell scenarios. The results validate the feasibility and accuracy of the proposed model, and confirm the severe influence of the intercell interference on the UL capacity. INDEX TERMS Unmanned aerial vehicles, cellular network, base station, uplink capacity , ergodic sum interference power.

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Section: Discussionmentioning

confidence: 99%

Enabling Capacity Estimation With Ergodic Interference Power in Cellular-Based Multiple UAV Systems

Zhao

Zhou

et al. 2020

IEEE Access

Self Cite

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“…Other cases can be similarly extracted. Note that our global motion extraction is inspired by [42] which proposes a sensor-assisted global motion estimation method. We share the same idea to estimate motion based on the projection model but our work focuses on working with codec for video compression and handle imperfect motion compensation.…”

Section: Global Motion Compensated Encodingmentioning

confidence: 99%

Towards Drone-Sourced Live Video Analytics via Adaptive-yet-Compatible Compression

Guo

Peng

2021

Proceedings of the 22nd International Workshop on Mobile Computing Systems and Applications

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In this work, we present DCC (Deeper-yet-Compatible Compression), one enabling technique for real-time drone-sourced edge-assisted video analytics built on top of the existing codec. DCC tackles an important technical problem to compress streamed video from the drone to the edge without scarifying accuracy and timeliness of video analytical tasks performed at the edge. DCC is inspired by the fact that not every bit in streamed video is equally valuable to video analytics, which opens new compression room over the conventional analytics-oblivious video codec technology. We exploit drone-specific context and intermediate hints from object detection to pursue adaptive fidelity needed to retain analytical quality. We have prototyped DCC in one showcase application of vehicle detection and validated its efficiency in representative scenarios. DCC has reduced transmission volume by 9.5-fold over the baseline approach and 19-683% over [1] with comparable detection accuracy.

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UAV Anti-Jamming Video Transmissions With QoE Guarantee: A Reinforcement Learning-Based Approach

Xiao

Ding

Huang

et al. 2021

IEEE Trans. Commun.

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Sensor-Assisted Global Motion Estimation for Efficient UAV Video Coding

Cited by 3 publications

References 10 publications

Enabling Capacity Estimation With Ergodic Interference Power in Cellular-Based Multiple UAV Systems

Enabling Capacity Estimation With Ergodic Interference Power in Cellular-Based Multiple UAV Systems

Towards Drone-Sourced Live Video Analytics via Adaptive-yet-Compatible Compression

UAV Anti-Jamming Video Transmissions With QoE Guarantee: A Reinforcement Learning-Based Approach

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