We base our work on the teleosemantic modelling of concepts as abilities implementing the distinct functions of recognition and classification. Accordingly, we model two types of concepts - substance concepts suited for object recognition exploiting visual properties, and classification concepts suited for classification of substance concepts exploiting linguistically grounded properties. The goal in this paper is to demonstrate that object recognition can be construed as classification of visual properties, as distinct from work in mainstream computer vision. Towards that, we present an object recognition process based on Ranganathan's four-phased faceted knowledge organization process, grounded in the teleosemantic distinctions of substance concept and classification concept. We also briefly introduce the ongoing project MultiMedia UKC, whose aim is to build an object recognition resource following our proposed process

翻译：因此,我们以两类概念为模型,即适合利用视觉特性进行物体识别的实质性概念,以及适合于利用语言特性进行物质概念分类的概念。本文件的目的是表明,物体识别可被理解为视觉特性的分类,有别于主流计算机愿景的工作。为此,我们提出了一个基于Ranganathan四阶段面对面知识组织过程的物体识别进程,其基础是物质概念和分类概念的遥测式区分。我们还简要介绍了正在进行的项目MultiMedia UKC,其目的是在我们拟议的过程之后建立一个物体识别资源。