MadEye: Boosting Live Video Analytics Accuracy with Adaptive Camera Configurations
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Abstract (arXiv)
Camera orientations (i.e., rotation and zoom) govern the content that a camera captures in a given scene, which in turn heavily influences the accuracy of live video analytics pipelines. However, existing analytics approaches leave this crucial adaptation knob untouched, instead opting to only alter the way that captured images from fixed orientations are encoded, streamed, and analyzed. We present MadEye, a camera-server system that automatically and continually adapts orientations to maximize accuracy for the workload and resource constraints at hand. To realize this using commodity pan-tilt-zoom (PTZ) cameras, MadEye embeds (1) a search algorithm that rapidly explores the massive space of orientations to identify a fruitful subset at each time, and (2) a novel knowledge distillation strategy to efficiently (with only camera resources) select the ones that maximize workload accuracy. Experiments on diverse workloads show that MadEye boosts accuracy by 2.9-25.7% for the same resource usage, or achieves the same accuracy with 2-3.7x lower resource costs.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 42 of its 117 references that are in the map. First posted on arXiv 4 Apr 2023.
Builds on
42 of 117 references.
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Built on by
Citing papers per year: 2024: 3; 2025: 4.
7 papers.
- 2024AxiomVision: Accuracy-Guaranteed Adaptive Visual Model Selection for Perspective-Aware Video Analyticscited by 4
- 2025AI Should Sense Better, Not Just Scale Bigger: Adaptive Sensing as a Paradigm Shiftcited by 3
- 2024Enabling Cross-Camera Collaboration for Video Analytics on Distributed Smart Camerascited by 1
- 2024AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applicationscited by 1
- 2025Legilimens: Performant Video Analytics on the System-on-Chip Edgecited by 0
- 2025ECCO: Leveraging Cross-Camera Correlations for Efficient Live Video Continuous Learningcited by 0
- 2025RedunCut: Measurement-Driven Sampling and Accuracy Performance Modeling for Low-Cost Live Video Analyticscited by 0
- 2025RedunCut: Measurement-Driven Sampling and Accuracy Performance Modeling for Low-Cost Live Video Analytics30 Dec 2025
- 2025ECCO: Leveraging Cross-Camera Correlations for Efficient Live Video Continuous Learning12 Dec 2025
- 2025AI Should Sense Better, Not Just Scale Bigger: Adaptive Sensing as a Paradigm Shift10 Jul 2025
- 2025Legilimens: Performant Video Analytics on the System-on-Chip Edge29 Apr 2025
- 2024AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications30 Dec 2024
- 2024AxiomVision: Accuracy-Guaranteed Adaptive Visual Model Selection for Perspective-Aware Video Analytics29 Jul 2024
- 2024Enabling Cross-Camera Collaboration for Video Analytics on Distributed Smart Cameras25 Jan 2024