Wireless video transmission over MIMO-OFDM using background modeling for video surveillance applications

Cajote, Rhandley D.; Ruangsang, Watchara; Aramvith, Supavadee; Prapinmongkolkarn, Prasit; Miyanaga, Yoshikazu; Onoye, Takao

doi:10.1109/iscit.2015.7458351

Cited by 1 publication

(2 citation statements)

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“…A lot of existing research has considered video coding and transmission schemes to improve the human visual quality [ 10 , 11 , 12 , 13 , 14 , 15 ]. The authors in [ 10 ] proposed a joint coding and transmission scheme to provide high quality video for human consumption.…”

Section: Introductionmentioning

confidence: 99%

“…Then in a server, the multiple videos were merged to one video with a wide viewing angle and high resolution, to provide high quality surveillance video for human consumption. In [ 11 ], a background-model-based wireless video transmission scheme was proposed to provide high quality of experience (QoE) for users. The foreground (like pedestrians) regions were detected in camera mode.…”

Section: Introductionmentioning

confidence: 99%

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Joint Source and Channel Rate Allocation over Noisy Channels in a Vehicle Tracking Multimedia Internet of Things System

Mei

Liu

et al. 2018

Sensors

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As an emerging type of Internet of Things (IoT), multimedia IoT (MIoT) has been widely used in the domains of healthcare, smart buildings/homes, transportation and surveillance. In the mobile surveillance system for vehicle tracking, multiple mobile camera nodes capture and upload videos to a cloud server to track the target. Due to the random distribution and mobility of camera nodes, wireless networks are chosen for video transmission. However, the tracking precision can be decreased because of degradation of video quality caused by limited wireless transmission resources and transmission errors. In this paper, we propose a joint source and channel rate allocation scheme to optimize the performance of vehicle tracking in cloud servers. The proposed scheme considers the video content features that impact tracking precision for optimal rate allocation. To improve the reliability of data transmission and the real-time video communication, forward error correction is adopted in the application layer. Extensive experiments are conducted on videos from the Object Tracking Benchmark using the H.264/AVC standard and a kernelized correlation filter tracking scheme. The results show that the proposed scheme can allocate rates efficiently and provide high quality tracking service under the total transmission rate constraints.

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