Ontology-based conditional random fields for object recognition
作者：
Highlights：
• A novel model for object recognition called Ontology-based CRF is proposed.
• It uses a multiple-level structure mimicking the subsumption ordering of Ontologies.
• Each level jointly categorizes the same set of objects with different granularity.
• Granularity ranges from specialized types (oven, fridge) to general ones (appliance).
• The proposal has been assessed with the Robot@Home and Cornell-RGBD datasets.
摘要
•A novel model for object recognition called Ontology-based CRF is proposed.•It uses a multiple-level structure mimicking the subsumption ordering of Ontologies.•Each level jointly categorizes the same set of objects with different granularity.•Granularity ranges from specialized types (oven, fridge) to general ones (appliance).•The proposal has been assessed with the Robot@Home and Cornell-RGBD datasets.
论文关键词：Object recognition,Conditional random fields,Ontologies,Probabilistic graphical models
论文评审过程：Received 30 July 2018, Revised 10 October 2018, Accepted 3 January 2019, Available online 9 January 2019, Version of Record 15 February 2019.
论文官网地址：https://doi.org/10.1016/j.knosys.2019.01.005
