NDLI: Probabilistic object identification through on-demand partial views

Content Provider	IEEE Xplore Digital Library
Author	Brandao, Susana Veloso, Manuela Costeira, Joao P.
Copyright Year	2014
Description	Author affiliation: Computer Science Department, Carnegie Mellon University, Pittsburgh, U.S.A. (Veloso, Manuela) \|\| Instituto Superior Técnico, Universidade de Lisboa, Av Rovisco Pais, Portugal (Brandao, Susana; Costeira, Joao P.)
Abstract	The current paper addresses the problem of object identification from multiple 3D partial views, collected from different view angles with the objective of disambiguating between similar objects. We assume a mobile robot equipped with a depth sensor that autonomously grasps an object from different positions, with no previous known pattern. The challenge is to efficiently combine the set of observations into a single classification. We approach the problem with a sequential importance resampling filter that allows to combine the sequence of observations and that, by its sampling nature, allows to handle the large number of possible partial views. In this context, we introduce innovations at the level of the partial view representation and at the formulation of the classification problem. We provide a qualitative comparison to support our representation and illustrate the identification process with a case study.
Starting Page	717
Ending Page	722
File Size	296940
Page Count	6
File Format	PDF
ISBN	9789897581335
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-05
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	SCITEPRESS
Subject Keyword	Three-dimensional displays Heating Noise Estimation Glass Robotic Vision Kernel Robots 3D Partial View Representation
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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