التفاصيل البيبلوغرافية
| العنوان: |
Detecting Contextual Anomalies by Discovering Consistent Spatial Regions |
| المؤلفون: |
Yang, Zhengye, Radke, Richard J. |
| سنة النشر: |
2025 |
| المجموعة: |
Computer Science |
| مصطلحات موضوعية: |
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence |
| الوصف: |
We describe a method for modeling spatial context to enable video anomaly detection. The main idea is to discover regions that share similar object-level activities by clustering joint object attributes using Gaussian mixture models. We demonstrate that this straightforward approach, using orders of magnitude fewer parameters than competing models, achieves state-of-the-art performance in the challenging spatial-context-dependent Street Scene dataset. As a side benefit, the high-resolution discovered regions learned by the model also provide explainable normalcy maps for human operators without the need for any pre-trained segmentation model. |
| نوع الوثيقة: |
Working Paper |
| URL الوصول: |
http://arxiv.org/abs/2501.08470 |
| رقم الانضمام: |
edsarx.2501.08470 |
| قاعدة البيانات: |
arXiv |