Towards Causal Physical Error Discovery in Video Analytics Systems
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866916262804717568 |
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| author | Zhao, Jinjin Shaowang, Ted Sintos, Stavos Krishnan, Sanjay |
| author_facet | Zhao, Jinjin Shaowang, Ted Sintos, Stavos Krishnan, Sanjay |
| contents | Video analytics systems based on deep learning models are often opaque and brittle and require explanation systems to help users debug. Current model explanation system are very good at giving literal explanations of behavior in terms of pixel contributions but cannot integrate information about the physical or systems processes that might influence a prediction. This paper introduces the idea that a simple form of causal reasoning, called a regression discontinuity design, can be used to associate changes in multiple key performance indicators to physical real world phenomena to give users a more actionable set of video analytics explanations. We overview the system architecture and describe a vision of the impact that such a system might have. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_17686 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards Causal Physical Error Discovery in Video Analytics Systems Zhao, Jinjin Shaowang, Ted Sintos, Stavos Krishnan, Sanjay Computer Vision and Pattern Recognition Video analytics systems based on deep learning models are often opaque and brittle and require explanation systems to help users debug. Current model explanation system are very good at giving literal explanations of behavior in terms of pixel contributions but cannot integrate information about the physical or systems processes that might influence a prediction. This paper introduces the idea that a simple form of causal reasoning, called a regression discontinuity design, can be used to associate changes in multiple key performance indicators to physical real world phenomena to give users a more actionable set of video analytics explanations. We overview the system architecture and describe a vision of the impact that such a system might have. |
| title | Towards Causal Physical Error Discovery in Video Analytics Systems |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2405.17686 |