IVCA: Inter-Relation-Aware Video Complexity Analyzer
IVCA: Inter-Relation-Aware Video Complexity Analyzer
电子技术应用
Junqi Liao,Yao Li,Li Li,Dong Liu,Zhuoyuan Li.IVCA: Inter-Relation-Aware Video Complexity Analyzer[EB/OL].(2024-06-28)[2025-10-25].https://arxiv.org/abs/2407.00280.点此复制
To address the real-time analysis requirements of video streaming
applications, we propose an innovative inter-relation-aware video complexity
analyzer (IVCA) to enhance the existing video complexity analyzer (VCA). The
IVCA overcomes the limitations of the VCA by incorporating inter-frame
relations, focusing on inter motion and reference structure. To begin with, we
improve the accuracy of temporal features by integrating feature-domain motion
estimation into the IVCA framework, which allows for a more nuanced
understanding of motion across frames. Furthermore, inspired by the
hierarchical reference structures utilized in modern codecs, we introduce
layer-aware weights that effectively adjust the contributions of frame
complexity across different layers, ensuring a more balanced representation of
video characteristics. In addition, we broaden the analysis of temporal
features by considering reference frames rather than relying solely on the
preceding frame, thereby enriching the contextual understanding of video
content. Experimental results demonstrate a significant enhancement in
complexity estimation accuracy achieved by the IVCA, coupled with a negligible
increase in time complexity, indicating its potential for real-time
applications in video streaming scenarios. This advancement not only improves
video processing efficiency but also paves the way for more sophisticated
analytical tools in video technology.
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