Robotics: Science and Systems X 2014
DOI: 10.15607/rss.2014.x.006
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Abstract: Abstract-Semantic labeling of RGB-D scenes is very important in enabling robots to perform mobile manipulation tasks, but different tasks may require entirely different sets of labels. For example, when navigating to an object, we may need only a single label denoting its class, but to manipulate it, we might need to identify individual parts. In this work, we present an algorithm that produces hierarchical labelings of a scene, following is-part-of and is-type-of relationships. Our model is based on a Conditi… Show more

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Cited by 62 publications
(45 citation statements)
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“…Many variants augment CRFs with latent variables in order to model hidden states, such as latent CRFs [33] that have been applied to object recognition [36,14,42], scene understanding [35], gesture recognition [40] and grounding natural language to robotic tasks [29]. However, in these models, the predefined latent space is discrete and small to keep the learning and inference tractable.…”
Section: Related Workmentioning
confidence: 99%
“…Many variants augment CRFs with latent variables in order to model hidden states, such as latent CRFs [33] that have been applied to object recognition [36,14,42], scene understanding [35], gesture recognition [40] and grounding natural language to robotic tasks [29]. However, in these models, the predefined latent space is discrete and small to keep the learning and inference tractable.…”
Section: Related Workmentioning
confidence: 99%
“…In the area of computer vision, some works have considered relating phrases and attributes to images and videos [39,15,26,25,21,50]. These works focus primarily on labeling the image/video by modeling the rich perceptual data rather than modeling the relations in the language and the entities in the environment.…”
Section: Related Workmentioning
confidence: 99%
“…While most methods use 2D visual information only [2], there are numerous 3D shape based recognition techniques [3,4], as well as methods that use both visual and shape information [5,6]. Object detection methods are essential for scene understanding [7], which has a number of applications in different fields, such as robotics [1] or augmented reality [8].…”
Section: Introductionmentioning
confidence: 99%