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An Intelligent Video Processing Architecture for Edge-cloud Video Streaming
Time
Location
Event Type
Research Manuscript
Virtual Programs
Hosted in Virtual Platform
Keywords
Design of Cyber-physical Systems and IoT
Topics
Design
DescriptionThis work proposes an intelligent video processing architecture for bandwidth-efficient edge-cloud video streaming. On receiving the bandwidth-saving low-quality video streaming in compressed format, the proposed architecture can perform direct DNN-based video enhancement, e.g., super-resolution and motion compensation, on streams without decompression. By utilizing the metadata motion vector and residual extracted from the encoded video, our workflow will significantly eliminate the unnecessary pixels being processed by the video-enhancing DNNs, and greatly promote the execution efficiency. The evaluation results on popular datasets show that our architecture achieves significant performance speedup over the traditional flow while producing accurate and high-quality videos on edge.