arXiv subjects

Yuxing Han

Publications and source records attributed to Yuxing Han.

57 records · Page 4Linked to original sources

arXiv2018

A Bayesian Approach to Block Structure Inference in AV1-based Multi-rate Video Encoding

Due to differences in frame structure, existing multi-rate video encoding algorithms cannot be directly adapted to encoders utilizing special reference frames such as AV1 without introducing substantial rate-distortion loss. To tackle this problem, we propose a novel bayesian block structure inference model inspired by a modification to an HEVC-based algorithm. It estimates the posterior probabilistic distributions of block partitioning, and adapts early terminations in the RDO procedure accordingly. Experimental results show that the proposed method provides flexibility for controlling the tradeoff between speed and coding efficiency, and can achieve an average time saving of 36.1% (up to 50.6%) with negligible bitrate cost.

cs.MM↗

arXiv2018

Fast Block Structure Determination in AV1-based Multiple Resolutions Video Encoding

The widely used adaptive HTTP streaming requires an efficient algorithm to encode the same video to different resolutions. In this paper, we propose a fast block structure determination algorithm based on the AV1 codec that accelerates high resolution encoding, which is the bottle-neck of multiple resolutions encoding. The block structure similarity across resolutions is modeled by the fineness of frame detail and scale of object motions, this enables us to accelerate high resolution encoding based on low resolution encoding results. The average depth of a block's co-located neighborhood is used to decide early termination in the RDO process. Encoding results show that our proposed algorithm reduces encoding time by 30.1%-36.8%, while keeping BD-rate low at 0.71%-1.04%. Comparing to the state-of-the-art, our method halves performance loss without sacrificing time savings.

cs.MM↗

arXiv2011

Weighted Centroid Algorithm for Estimating Primary User Location: Theoretical Analysis and Distributed Implementation

Information about primary transmitter location is crucial in enabling several key capabilities in cognitive radio networks, including improved spatio-temporal sensing, intelligent location-aware routing, as well as aiding spectrum policy enforcement. Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only the received signal strength information, which makes it simple to implement and robust to variations in the propagation environment. In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance, correlation distance and inaccuracy of sensor node positioning. Using this analysis, we quantify the robustness of WCL to various physical conditions and provide design guidelines, such as node placement and spacing, for the practical deployment of WCL. We also propose a power-efficient method for implementing WCL through a distributed cluster-based algorithm, that achieves comparable accuracy with its centralized counterpart.

cs.PF↗