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检索条件"机构=Computer Vision and Active Perception Laboratory"
58 条 记 录,以下是21-30 订阅
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Novelty Detection from an Ego-Centric Perspective
Novelty Detection from an Ego-Centric Perspective
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IEEE Conference on computer vision and Pattern Recognition
作者: Omid Aghazadeh Josephine Sullivan Stefan Carlsson Computer Vision and Active Perception Laboratory KTH
This paper demonstrates a system for the automatic extraction of novelty in images captured from a small video camera attached to a subject's chest, replicating his visual perspective, while performing activities ... 详细信息
来源: 评论
Grasping unknown objects using an Early Cognitive vision system for general scene understanding
Grasping unknown objects using an Early Cognitive Vision sys...
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2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
作者: Mila Popović Gert Kootstra Jimmy Alison Jørgensen Danica Kragic Norbert Krüger Cognitive Vision laboratory The Mærsk Mc-Kinney Møller Institute University of Southern Denmark Odense Denmark Computer Vision and Active Perception laboratory CSC Royal Institute of Technology (KTH) Stockholm Sweden
Grasping unknown objects based on real-world visual input is a challenging problem. In this paper, we present an Early Cognitive vision system that builds a hierarchical representation based on edge and texture inform... 详细信息
来源: 评论
Enhanced visual scene understanding through human-robot dialog
Enhanced visual scene understanding through human-robot dial...
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2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
作者: Matthew Johnson-Roberson Jeannette Bohg Gabriel Skantze Joakim Gustafson Rolf Carlson Babak Rasolzadeh Danica Kragic Centre of Autonomous Systems Computational Vision and Active Perception Laboratory Sweden Department for Speech Music and Hearing Institutes part of School of Computer Science KTH in Stockholm Sweden
We propose a novel human-robot-interaction framework for robust visual scene understanding. Without any a-priori knowledge about the objects, the task of the robot is to correctly enumerate how many of them are in the... 详细信息
来源: 评论
Fast and Automatic Detection and Segmentation of unknown objects
Fast and Automatic Detection and Segmentation of unknown obj...
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IEEE-RAS International Conference on Humanoid Robots
作者: Gert Kootstra Niklas Bergström Danica Kragic The Computer Vision and Active Perception Laboratory Center of Autonomous Systems Stockholm Sweden
This paper focuses on the fast and automatic detection and segmentation of unknown objects in unknown environments. Many existing object detection and segmentation methods assume prior knowledge about the object or hu... 详细信息
来源: 评论
Representations for object grasping and learning from experience
Representations for object grasping and learning from experi...
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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems
作者: Oscar J. Rubio Kai Huebner Danica Kragic Computer Vision and Active Perception Laboratory Centre of Autonomous Systems School of Computer Science and Communication KTH Stockholm Sweden
We study two important problems in the area of robot grasping: i) the methodology and representations for grasp selection on known and unknown objects, and ii) learning from experience for grasping of similar objects.... 详细信息
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Task modeling in imitation learning using latent variable models
Task modeling in imitation learning using latent variable mo...
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IEEE-RAS International Conference on Humanoid Robots
作者: Carl Henrik Ek Dan Song Kai Huebner Danica Kragic Computer Vision & Active Perception Laboratory Center of Autonomous Systems KTH Royal Institute of Technology Stockholm Sweden
An important challenge in robotic research is learning and reasoning about different manipulation tasks from scene observations. In this paper we present a probabilistic model capable of modeling several different typ... 详细信息
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ICE matching, a novel approach for localization problem
ICE matching, a novel approach for localization problem
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International Conference on Control, Automation and Systems ( ICCAS)
作者: Maziar A. Sharbafi Sanaz Taleghani Edriss Esmaeili Abolfazl T. Haghighat Omid Aghazadeh Department of Electrical and Computer Engineering Azad University of Qazvin Qazvin Iran Computer Vision and Active Perception(CVAP) laboratory KTH Stockholm Sweden
This paper presents a novel technique for scan matching. The method is based on the family of feature to feature matching approaches. Our innovative method named ICE matching leads to a fast and accurate solution to s... 详细信息
来源: 评论
Saliency ranking for benthic survey using underwater images
Saliency ranking for benthic survey using underwater images
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International Conference on Control, Automation, Robotics and vision (ICARCV)
作者: Matthew Johnson-Roberson Oscar Pizarro Stefan Williams Computational Vision and Active Perception Laboratory School of Computer Science and Communication Royal Institute of Technology Sweden ARC Centre of Excellence of Autonomous Systems Australian Centre of Field Robotics University of Sydney Australia
This paper presents a novel architecture for a classification system based on the visual saliency of images. The work is motivated by the difficulty of reviewing large numbers of images as a human operator in the cont... 详细信息
来源: 评论
Grasping familiar objects using shape context
Grasping familiar objects using shape context
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International Conference on Advanced Robotics (ICAR)
作者: Jeannette Bohg Danica Kragic Centre of Autonomous Systems Computer Vision and Active Perception Laboratory Stockholm Sweden
We present work on vision based robotic grasping. The proposed method relies on extracting and representing the global contour of an object in a monocular image. A suitable grasp is then generated using a learning fra... 详细信息
来源: 评论
Modeling Image Context Using Object Centered Grid
Modeling Image Context Using Object Centered Grid
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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)
作者: Sobhan Naderi Parizi Ivan Laptev Alireza Tavakoli Targhi Computer Vision and Active Perception Laboratory Royal Institute of Technology (KTH) Stockholm Sweden INRIA / École Normale Superieure Paris France
Context plays a valuable role in any image understanding task confirmed by numerous studies which have shown the importance of contextual information in computer vision tasks, like object detection, scene classificati... 详细信息
来源: 评论