تقرير
Hybrid Primal Sketch: Combining Analogy, Qualitative Representations, and Computer Vision for Scene Understanding
العنوان: | Hybrid Primal Sketch: Combining Analogy, Qualitative Representations, and Computer Vision for Scene Understanding |
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المؤلفون: | Forbus, Kenneth D., Chen, Kezhen, Xu, Wangcheng, Usher, Madeline |
سنة النشر: | 2024 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence |
الوصف: | One of the purposes of perception is to bridge between sensors and conceptual understanding. Marr's Primal Sketch combined initial edge-finding with multiple downstream processes to capture aspects of visual perception such as grouping and stereopsis. Given the progress made in multiple areas of AI since then, we have developed a new framework inspired by Marr's work, the Hybrid Primal Sketch, which combines computer vision components into an ensemble to produce sketch-like entities which are then further processed by CogSketch, our model of high-level human vision, to produce both more detailed shape representations and scene representations which can be used for data-efficient learning via analogical generalization. This paper describes our theoretical framework, summarizes several previous experiments, and outlines a new experiment in progress on diagram understanding. Comment: 16 pages, 6 figures |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2407.04859 |
رقم الأكسشن: | edsarx.2407.04859 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |