Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships
Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships
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发表时间：
2009-12
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通讯作者：
Tomasz Malisiewicz;Alexei A. Efros
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作者：
Tomasz Malisiewicz;Alexei A. Efros
上下文的使用对于计算机视觉中的场景理解至关重要，其中对象的识别是由局部外观和对象与场景（上下文）其他元素的关系驱动的。大多数当前的方法依赖于将对象类别之间的关系建模作为上下文的来源。在本文中，我们试图超越类别，提供更丰富的基于外观的上下文模型。我们提出了一个基于示例的对象及其关系模型，即Visual Memex，它对对象实例之间的局部外观和2D空间上下文进行编码。我们根据托拉尔巴提出的上下文挑战对基于基线分类的系统评估我们的模型。我们的实验表明，超越类别进行上下文建模似乎是非常有益的，并且可能是场景理解系统中关键的缺失成分。
The use of context is critical for scene understanding in computer vision, where the recognition of an object is driven by both local appearance and the object's relationship to other elements of the scene (context). Most current approaches rely on modeling the relationships between object categories as a source of context. In this paper we seek to move beyond categories to provide a richer appearance-based model of context. We present an exemplar-based model of objects and their relationships, the Visual Memex, that encodes both local appearance and 2D spatial context between object instances. We evaluate our model on Torralba's proposed Context Challenge against a baseline category-based system. Our experiments suggest that moving beyond categories for context modeling appears to be quite beneficial, and may be the critical missing ingredient in scene understanding systems.