IVCA: Inter-Relation-Aware Video Complexity Analyzer
Junqi Liao, Yao Li, Zhuoyuan Li, Li Li, Dong Liu

TL;DR
The paper introduces IVCA, a novel real-time video complexity analyzer that incorporates inter-frame relations and hierarchical reference structures to improve accuracy without significant computational overhead.
Contribution
It presents a new inter-relation-aware framework that enhances temporal feature analysis and layer-aware weighting, advancing real-time video complexity estimation methods.
Findings
Significant accuracy improvement in complexity estimation.
Negligible increase in computational time.
Potential for real-time video streaming applications.
Abstract
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…
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Taxonomy
TopicsAnomaly Detection Techniques and Applications · Cell Image Analysis Techniques
