Dynamic Computation Off-loading and Control based on Occlusion Detection in Drone Video Analytics
Dynamic Computation Off-loading and Control based on Occlusion Detection in Drone Video Analytics
复制标题
无人机视频分析中基于遮挡检测的动态计算卸载和控制
DOI：
10.1145/3369740.3369793
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Palaniappan, Kannappan
中科院分区：
文献类型：
--
作者：
Ramisetty, Rajeswara Rao;Qu, Chengyi;Aktar, Rumana;Wang, Songjie;Calyam, Prasad;Palaniappan, Kannappan
无人驾驶飞行器（uav）或配备摄像头的无人机被广泛用于危险地点的监视、灾难响应和打击犯罪等不同场景。相关的视频流/分析需要实时无人机与地面控制站（GCS）的通信和计算协调，以实现所需的用户体验质量（QoE）。在由于网络瓶颈导致视频质量可能受到遮挡（例如，图像失真、帧延迟）影响的情况下，需要动态地决定计算卸载和网络协议，以便为现实世界的应用目的正确处理视频数据。在本文中，我们提出了一种新颖的以功能为中心的计算方法，该方法可以帮助用户执行无人机视频分析，以评估广域场景以制定行动计划。我们的方法包括处理影响高分辨率/低分辨率视频捕获切换的网络障碍，或改变摄像机方向以有效评估场景。它还具有一种新的基于遮挡检测的视频质量增强算法，该算法适用于与图像失真和帧延迟相关的视频损伤。我们的实验结果表明，我们的方法可以有效地选择合适的网络协议（即TCP/HTTP， UDP/RTP， QUIC），并协调无人机上的摄像机控制，以及在有限的边缘计算资源下视频分析的计算卸载。在不同的网络条件下，从遮挡率和处理时间方面显示了我们的视频质量增强算法在计算卸载方面的性能改进。
Unmanned Aerial Vehicles (UAVs) or drones equipped with cameras are extensively used in different scenarios such as surveillance of hazardous locations, disaster response and crime fighting. The related video streaming/analytics requires real-time drone-to-Ground Control Station (GCS) communication and computation co-ordination for desired user Quality of Experience (QoE). In situations where the quality of the video can be affected by occlusions (e.g., image distortion, frame stalling) due to network bottlenecks, there is a need to dynamically make decisions on the computation offloading and networking protocols in order to properly handle the video data for real world application purposes. In this paper, we propose a novel function-centric computing approach that helps a user to perform drone video analytics to assess a wide-area scene to chart a plan of action. Our approach involves handling network impairments affecting the switching between high resolution/low resolution video capture, or change of camera direction for assessment of the scene effectively. It also features a novel video quality enhancing algorithm based on occlusion-detection that adapts to video impairments related to image distortion and frame stalling. Our experiment results from a realistic testbed show that our approach can efficiently choose the suitable networking protocols (i.e., TCP/HTTP, UDP/RTP, QUIC) and orchestrate both the camera control on the drone, and the computation off-loading of the video analytics over limited edge computing resources. The performance improvements for computation off-loading involving our video quality enhancing algorithm are shown for different network conditions in terms of occlusion rate and processing times.
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影响因子：
7.3
作者：
Huy Trinh;P. Calyam;D. Chemodanov;Shizeng Yao;Qing Lei;Fan Gao;K. Palaniappan
通讯作者：
Huy Trinh;P. Calyam;D. Chemodanov;Shizeng Yao;Qing Lei;Fan Gao;K. Palaniappan
DOI：
--
发表时间：
2019
期刊：
Conference on Innovation in Clouds, Internet and Networks
影响因子：
--
作者：
Michael Seufert;R. Schatz;Nikolas Wehner;P. Casas
通讯作者：
P. Casas
DOI：
10.1109/infocom.2019.8737498
发表时间：
2019-04
期刊：
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications
影响因子：
--
作者：
D. Chemodanov;P. Calyam;Flavio Esposito
通讯作者：
D. Chemodanov;P. Calyam;Flavio Esposito
用于实时无人机视频分析的基于策略、以功能为中心的计算卸载
DOI：
10.1109/lanman.2019.8847112
发表时间：
2019
期刊：
IEEE Symposium on Local and Metropolitan Networks (LANMAN
影响因子：
--
作者：
Chemodanov, Dmitrii;Qu, Chengyi;Opeoluwa, Osunkoya;Wang, Songjie;Calyam, Prasad
通讯作者：
Calyam, Prasad
将视频帧与文本关联
DOI：
--
发表时间：
2003
期刊：
影响因子：
--
作者：
Pinar Duygulu;H. Wactlar
通讯作者：
H. Wactlar