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Ahmad Vakili

Publications and source records attributed to Ahmad Vakili.

3 recordsLinked to original sources

Power-Efficient Video Streaming on Mobile Devices Using Optimal Spatial Scaling

This paper derives optimal spatial scaling and rate control parameters for power-efficient wireless video streaming on portable devices. A video streaming application is studied, which receives a high-resolution and high-quality video stream from a remote server and displays the content to the end-user.We show that the resolution of the input video can be adjusted such that the quality-power trade-off is optimized. Making use of a power model from the literature and subjective quality evaluation using a perceptual metric, we derive optimal combinations of the scaling factor and the rate-control parameter for encoding. For HD sequences, up to 10% of power can be saved at negligible quality losses and up to 15% of power can be saved at tolerable distortions. To show general validity, the method was tested for Wi-Fi and a mobile network as well as for two different smartphones.

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Efficient coding of 360° videos exploiting inactive regions in projection formats

This paper presents an efficient method for encoding common projection formats in 360$^\circ$ video coding, in which we exploit inactive regions. These regions are ignored in the reconstruction of the equirectangular format or the viewport in virtual reality applications. As the content of these pixels is irrelevant, we neglect the corresponding pixel values in ratedistortion optimization, residual transformation, as well as inloop filtering and achieve bitrate savings of up to 10%.

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Power Modeling for Virtual Reality Video Playback Applications

This paper proposes a method to evaluate and model the power consumption of modern virtual reality playback and streaming applications on smartphones. Due to the high computational complexity of the virtual reality processing toolchain, the corresponding power consumption is very high, which reduces operating times of battery-powered devices. To tackle this problem, we analyze the power consumption in detail by performing power measurements. Furthermore, we construct a model to estimate the true power consumption with a mean error of less than 3.5%. The model can be used to save power at critical battery levels by changing the streaming video parameters. Particularly, the results show that the power consumption is significantly reduced by decreasing the input video resolution.

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