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Real-Time Mobile Video Compression and Streaming: Live Video from Mobile Devices over Cell Phone Networks

Uti, Ngozi V.

Abstract Details

2011, PhD, University of Cincinnati, Engineering and Applied Science: Computer Science and Engineering.

The limited computing resources on mobile phones, the demands of real-time requirements, and the variable and error-prone nature of the bandwidth of cell phone networks make the task of streaming live video from cell phones very challenging. As such, computational simplicity and efficiency are a requirement for video encoders on mobile devices. This research presents core components of a mobile video compression algorithm that has been developed in this project to compress real-time video from cell phones. This work shows how the careful selection of video compression components can be used to strike a delicate balance between the computationally complex nature of video compression and the efficient utilization of the limited computing resources available on cell phones. Although optimality is never claimed, a method for compressing and streaming real-time video of 15 frames per second has been developed. The video encoder uses 5-3 wavelet transformation and a new subband aligned integer run-length encoding technique to compress video in real-time on mobile devices. The wavelet video encoder is adaptive, highly scalable, and can gracefully adjust video compression levels to match changing cell phone network bandwidth conditions.

Further, because of the variability of the bandwidth of cell phone networks, the efficient streaming of real-time video over cell phone networks requires the ability to adapt the quality and amount of video being streamed to the available bandwidth. This research shows that without such adaptability, video frames will be dropped. Experiments presented herein show that without an adaptive framework over 50% of the video frames can be dropped. In response to this challenge, this research implements an application layer framework for the control of real-time streaming video originating from mobile devices to better utilize available bandwidth. The approach taken here aims to align the quality and transmission rate of live streaming video with the capabilities of cell phone networks.

Using decision making and feedback from the receiving video decoder, this real-time mobile streaming video framework is able to sense network conditions and effectively predict the available bandwidth. This adaptive framework utilizes the scalable wavelet video encoder for video compression. In conjunction with the wavelet video encoder on the mobile device, the framework adapts in real-time the video quality and video frames transmitted per second to achieve a near 100% delivery rate. This work provides a thorough description of this framework along with numerous experimental results. Presented is a detailed examination of the features of the adaptive framework and how they relate to cell phone network conditions, the video being streamed, and the mobile computing resources available on the mobile device.

Yizong Cheng, PhD (Committee Chair)
Richard Fox, PhD (Committee Member)
Fred Annexstein, PhD (Committee Member)
Raj Bhatnagar, PhD (Committee Member)
Dieter Schmidt, PhD (Committee Member)
147 p.

Recommended Citations

Citations

  • Uti, N. V. (2011). Real-Time Mobile Video Compression and Streaming: Live Video from Mobile Devices over Cell Phone Networks [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1302550980

    APA Style (7th edition)

  • Uti, Ngozi. Real-Time Mobile Video Compression and Streaming: Live Video from Mobile Devices over Cell Phone Networks. 2011. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1302550980.

    MLA Style (8th edition)

  • Uti, Ngozi. "Real-Time Mobile Video Compression and Streaming: Live Video from Mobile Devices over Cell Phone Networks." Doctoral dissertation, University of Cincinnati, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1302550980

    Chicago Manual of Style (17th edition)