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检索条件"机构=Computer Vision and Active Perception Laboratory"

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Object recognition using saliency maps and HTM learning

Object recognition using saliency maps and HTM learning

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2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012

作者： Kostavelis, Ioannis Nalpantidis, Lazaros Gasteratos, Antonios Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Vas. Sofias 12 GR-67100 Xanthi Greece Computer Vision and Active Perception Lab. Centre for Autonomous Systems Royal Institute of Technology - KTH SE-100 44 Stockholm Sweden

ISBN: (纸本)9781457717741

In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems. © 2012 IEEE.

关键词： Object recognition

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Integrating object and grasp recognition for dynamic scene interpretation

Integrating object and grasp recognition for dynamic scene i...

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International Conference on Advanced Robotics (ICAR)

作者： S. Ekvall D. Kragic Computational Vision and Active Perception Laboratory Centre for Autonomous Systems Department of Numerical Analysis and Computer Science Royal Institute of Technology Stockholm Sweden

Understanding and interpreting dynamic scenes and activities is a very challenging problem. In this paper, we present a system capable of learning robot tasks from demonstration. Classical robot task programming requires an experienced programmer and a lot of tedious work. In contrast, programming by demonstration is a flexible framework that reduces the complexity of programming robot tasks, and allows end-users to demonstrate the tasks instead of writing code. We present our recent steps towards this goal. A system for learning pick-and-place tasks by manually demonstrating them is presented. Each demonstrated task is described by an abstract model involving a set of simple tasks such as what object is moved, where it is moved, and which grasp type was used to move it

关键词： Layout Robot programming Writing Humans Sensor phenomena and characterization Object recognition computer vision Laboratories Numerical analysis computer science

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Monocular real-time 3D articulated hand pose estimation

Monocular real-time 3D articulated hand pose estimation

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IEEE-RAS International Conference on Humanoid Robots

作者： Javier Romero Hedvig Kjellström Danica Kragic Computational Vision and Active Perception Laboratory Centre for Autonomous Systems School of Computer Science and Communication KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781424445875

Markerless, vision based estimation of human hand pose over time is a prerequisite for a number of robotics applications, such as learning by demonstration (LbD), health monitoring, teleoperation, human-robot interaction. It has special interest in humanoid platforms, where the number of degrees of freedom makes conventional programming challenging. Our primary application is LbD in natural environments where the humanoid robot learns how to grasp and manipulate objects by observing a human performing a task. This paper presents a method for continuous vision based estimation of human hand pose. The method is non-parametric, performing a nearest neighbor search in a large database (100000 entries) of hand pose examples. The main contribution is a real time system, robust to partial occlusions and segmentation errors, that provides full hand pose recognition from markerless data. An additional contribution is the modeling of constraints based on temporal consistency in hand pose, without explicitly tracking the hand in the high dimensional pose space. The pose representation is rich enough to enable a descriptive human-to-robot mapping. Experiments show the pose estimation to be more robust and accurate than a non-parametric method without temporal constraints.

关键词： Humanoid robots Real time systems Robustness Human robot interaction Robot vision systems Fingers computer vision computer science Application software computerized monitoring

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Integrating task-directed plaiming with reactive object recognition 12

Integrating task-directed plaiming with reactive object reco...

引用

Intelligent Robots and computer vision XII: Algorithms and Techniques 1993

作者： Dickinson, Sven Stevenson, Suzanne Amdur, Eugene Tsotsos, John Olsson, Lars Department of Computer Science University of Toronto 6 King's College Rd. TorontoONM5S1A4 Canada Computational Vision and Active Perception Laboratory Dept. of Numerical Analysis and Computing Science Royal Institute of Tecimology StockholmS-10044 Sweden

We describe a robot vision system that achieves complex object recognition with two layers of behaviors, performing the tasks of planning and object recognition, respectively. The recognition layer is a pipeline in which successive stages take in images from a stereo head, recover relevant features, build intermediate representations, and deposit 3-D objects into a world model. Each stage is an independent process that reacts automatically to output from the previous stage. This reactive system operates continuously and autonomously to construct the robot's 3-D model of the environment. Sitting above the recognition pipeline is the planner which is responsible for populating the world model with objects that satisfy the high-level goals of the system. For example, upon examination of the world model, the planner can decide to direct the head to another location, gating new images into the recognition pipeline, causing new objects to be deposited into the world model. Alternatively, the planner can alter the recognition behavior of the pipeline so that objects of a certain type or at a certain location appear in the world model. © 1993 SPIE.

关键词： Pipelines

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Many-to-many feature matching using spherical coding of directed graphs 8

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8th European Conference on computer vision, ECCV 2004

作者： Fatili Demirci, M. Shokoufandeh, Ali Dickinson, Sven Keselman, Yakov Bretzner, Lars Department of Computer Science Drexel University PhiladelphiaPA19104 United States Department of Computer Science University of Toronto TorontoONM5S 3G4 Canada School of Computer Science Telecommunications and Information Systems DePaul University ChicagoIL60604 United States Computational Vision and Active Perception Laboratory Department Of Numerical Analysis and Computer Science KTH Stockholm Sweden

ISBN: (纸本)3540219846

Abstract. In recent work, we presented a framework for many-to-many matching of multi-scale feature hierarchies, in which features and their relations were captured in a vertex-labeled, edge-weighted directed graph. The algorithm was based on a metric-tree representation of labeled graphs and their metric embedding into normed vector spaces, using the embedding algorithm of Matousek [13]. However, the method was limited by the fact that two graphs to be matched were typically embedded into vector spaces with different dimensionality. Before the embeddings could be matched, a dimensionality reduction technique (PCA) was required, which was both costly and prone to error. In this paper, we introduce a more efficient embedding procedure based on a spherical coding of directed graphs. The advantage of this novel embedding technique is that it prescribes a single vector space into which both graphs are embedded. This reduces the problem of directed graph matching to the problem of geometric point matching, for which efficient many-to-many matching algorithms exist, such as the Earth Mover's Distance. We apply the approach to the problem of multi-scale, view-based object recognition, in which an image is decomposed into a set of blobs and ridges with automatic scale selection. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Directed graphs

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active object recognition integrating attention and viewpoint control 3rd

引用

3rd European Conference on computer vision, ECCV 1994

作者： Dickinson, Sven J. Christensen, Henrik I. Tsotsos, John Olofsson, Göran Dept. of Computer Science University of Toronto 6 King’s College Rd. TorontoONM5S 1A4 Canada Laboratory of Image Analysis IES Aalborg University AalborgDK-9220 Denmark Computational Vision and Active Perception Laboratory Royal Institute of Technology StockholmS-100 44 Sweden

ISBN: (纸本)9783540579571

We present an active object recognition strategy which combines the use of an attention mechanism for focusing the search for a 3-D object in a 2-D image, with a viewpoint control strategy for disambiguating recovered object features. The attention mechanism consists of a probabilistic search through a hierarchy of predicted feature observations, taking objects into a set of regions classified according to the shapes of their bounding contours. If the features recovered during the attention phase do not provide a unique mapping to the 3-D object being searched, the probabilistic feature hierarchy can be used to guide the camera to a new viewpoint from where the object can be disambiguated. © Springer-Verlag Berlin Heidelberg 1994.

关键词： Object recognition

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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 information, which is a sparse but powerful description of the scene. Based on this representation we generate edge-based and surface-based grasps. The results show that the method generates successful grasps, that the edge and surface information are complementary, and that the method can deal with more complex scenes. We furthermore present a benchmark for visual-based grasping.

关键词： Grasping Three dimensional displays Shape Visualization Surface texture Image color analysis Machine vision

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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 scene and segment them from the background. Our approach builds on top of state-of-the-art computer vision methods, generating object hypotheses through segmentation. This process is combined with a natural dialog system, thus including a `human in the loop' where, by exploiting the natural conversation of an advanced dialog system, the robot gains knowledge about ambiguous situations. We present an entropy-based system allowing the robot to detect the poorest object hypotheses and query the user for arbitration. Based on the information obtained from the human-robot dialog, the scene segmentation can be re-seeded and thereby improved. We present experimental results on real data that show an improved segmentation performance compared to segmentation without interaction.

关键词： Robots Entropy Humans Three dimensional displays Histograms Machine vision Image analysis

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Fast shape-based road sign detection for a driver assistance system

Fast shape-based road sign detection for a driver assistance...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： G. Loy N. Barnes Computer Vision and Active Perception Laboratory Royal Institute of Technology (KTH) Stockholm Sweden Autonomous Systems and Sensor Technologies Program National ICT Australia Canberra Australia

A new method is presented for detecting triangular, square and octagonal road signs efficiently and robustly. The method uses the symmetric nature of these shapes, together with the pattern of edge orientations exhibited by equiangular polygons with a known number of sides, to establish possible shape centroid locations in the image. This approach is invariant to in-plane rotation and returns the location and size of the shape detected. Results on still images show a detection rate of over 95%. The method is efficient enough for real-time applications, such as on-board-vehicle sign detection.

关键词： Shape Road safety Detectors Image segmentation Robustness Image edge detection Australia Pixel Voting computer vision

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Object recognition using saliency maps and HTM learning

Object recognition using saliency maps and HTM learning

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Ioannis Kostavelis Lazaros Nalpantidis Antonios Gasteratos Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece Computer Vision and Active Perception Laboratory Centre for Autonomous Systems Royal Institute of Technology Stockholm Sweden

关键词： Correlation Quantization Vectors Accuracy Support vector machines Object recognition Humans

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