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

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Novelty detection from an ego-centric perspective

Novelty detection from an ego-centric perspective

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作者： Aghazadeh, Omid Sullivan, Josephine Carlsson, Stefan Computer Vision and Active Perception Laboratory KTH Sweden

ISBN: (纸本)9781457703942

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 which are repeated daily. Novelty is detected when a (sub)sequence cannot be registered to previously stored sequences captured while performing the same daily activity. Sequence registration is performed by measuring appearance and geometric similarity of individual frames and exploiting the invariant temporal order of the activity. Experimental results demonstrate that this is a robust way to detect novelties induced by variations in the wearer's ego-motion such as stopping and talking to a person. This is an essentially new and generic way of automatically extracting information of interest to the camera wearer and can be used as input to a system for life logging or memory support. © 2011 IEEE.

关键词： Video cameras

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Social Affordance Tracking over Time - A Sensorimotor Account of False-Belief Tasks 38

Social Affordance Tracking over Time - A Sensorimotor Accoun...

引用

38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016

作者： Bütepage, Judith Kjellström, Hedvig Kragic, Danica Computer Vision and Active Perception Laboratory CSC KTH Stockholm Sweden

ISBN: (纸本)9780991196739

False-belief task have mainly been associated with the explanatory notion of the theory of mind and the theory-theory. However, it has often been pointed out that this kind of high-level reasoning is computational and time expensive. During the last decades, the idea of embodied intelligence, i.e. complex behavior caused by sensorimotor contingencies, has emerged in both the fields of neuroscience, psychology and artificial intelligence. Viewed from this perspective, the failing in a false-belief test can be the result of the impairment to recognize and track others' sensorimotor contingencies and affordances. Thus, social cognition is explained in terms of low-level signals instead of high-level reasoning. In this work, we present a generative model for optimal action selection which simultaneously can be employed to make predictions of others' actions. As we base the decision making on a hidden state representation of sensorimotor signals, this model is in line with the ideas of embodied intelligence. We demonstrate how the tracking of others' hidden states can give rise to correct false-belief inferences, while a lack thereof leads to failing. With this work, we want to emphasize the importance of sensorimotor contingencies in social cognition, which might be a key to artificial, socially intelligent systems. © 2016 Proceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016. All rights reserved.

关键词： Decision making

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Strategies for object manipulation using foveal and peripheral vision

Strategies for object manipulation using foveal and peripher...

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Fourth IEEE International Conference on computer vision Systems, ICVS'06

作者： Kragic, Danica Björkman, Mårten Computer Vision and Active Perception Laboratory Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)0769525067

Visual feedback is used extensively in robotics and application areas range from human-robot interaction to object grasping and manipulation. There have been a number of examples of how to develop different components required by the above applications and very few general vision systems capable of performing a variety of tasks. In this paper, we concentrate on vision strategies for robotic manipulation tasks in a domestic environment. In particular, given fetch-and-carry type of tasks, the issues related to the whole detect-approach-grasp loop are considered. We deal with the problem of flexibility and robustness by using monocular and binocular visual cues and their integration. We demonstrate real-time disparity estimation, object recognition and pose estimation. We also show how a combination offoveal and peripheral vision system can be combined in order to provide a wide, low resolution and narrow, high resolution field of view. © 2006 IEEE.

关键词： computer vision

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Novelty Detection from an Ego-Centric Perspective

Novelty Detection from an Ego-Centric Perspective

引用

IEEE Conference on computer vision and Pattern Recognition

作者： Omid Aghazadeh Josephine Sullivan Stefan Carlsson Computer Vision and Active Perception Laboratory KTH

ISBN: (纸本)9781457703942

关键词： Novelty automatic extracting Video cameras visual perspective geometric similarity Speaking optical coherence tomography angiography device system parameter Persons stopping Perspective

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Estimating Attention in Exhibitions Using Wearable Cameras

Estimating Attention in Exhibitions Using Wearable Cameras

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International Conference on Pattern Recognition

作者： Ali S. Razavian Omid Aghazadeh Josephine Sullivan Stefan Carlsson KTH Computer Vision and Active Perception Laboratory Sweden

ISBN: (纸本)9781479952106

This paper demonstrates a system for automatic detection of visual attention and identification of salient items at exhibitions (e.g. museum or an auction). The method is offline and is done on a video captured by a head mounted camera. Towards the estimation of attention, we define the notions of "saliency" and "interestingness" for an exhibition items. Our method is a combination of multiple state of the art techniques from different vision tasks such as tracking, image matching and retrieval. Many experiments are conducted to evaluate multiple aspects of our method. The method has proven to be robust to image blur, occlusion, truncation, and dimness. The experiments shows strong performance for the tasks of matching items, estimating focus frames and detecting salient and interesting items. This can be useful to the commercial vendors and museum curators and help them to understand which items are appealing more to the visitors.

关键词： Cameras Vectors Head Support vector machines Robustness Feature extraction Optical imaging

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Multi view registration for novelty/background separation

Multi view registration for novelty/background separation

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Omid Aghazadeh Josephine Sullivan Stefan Carlsson Computer Vision and Active Perception laboratory Royal Institute of Technology Sweden

We propose a system for the automatic segmentation of novelties from the background in scenarios where multiple images of the same environment are available e.g. obtained by wearable visual cameras. Our method finds the pixels in a query image corresponding to the underlying background environment by comparing it to reference images of the same scene. This is achieved despite the fact that all the images may have different viewpoints, significantly different illumination conditions and contain different objects - cars, people, bicycles, etc. - occluding the background. We estimate the probability of each pixel, in the query image, belonging to the background by computing its appearance inconsistency to the multiple reference images. We then, produce multiple segmentations of the query image using an iterated graph cuts algorithm, initializing from these estimated probabilities and consecutively combine these segmentations to come up with a final segmentation of the background. Detection of the background in turn highlights the novel pixels. We demonstrate the effectiveness of our approach on a challenging outdoors data set.

关键词： Image segmentation Vectors Labeling Cameras Lighting Estimation Logistics

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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 framework where prototypical grasping points are learned from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labeled synthetic images. Our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects. Furthermore, we will show how our representation supports the inference of a full grasp configuration.

关键词： Humans Robot kinematics Robot vision systems Supervised learning Object detection Cameras Shape control computer vision Laboratories Prototypes

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DirectSVM: a fast and simple support vector machine perceptron

DirectSVM: a fast and simple support vector machine perceptr...

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IEEE Workshop on Neural Networks for Signal Processing

作者： D. Roobaert Computer Vision and Active Perception laboratory Royal Institute of Technology Stockholm Sweden

We propose a simple implementation of the support vector machine (SVM) for pattern recognition, that is not based on solving a complex quadratic optimization problem. Instead we propose a simple, iterative algorithm that is based on a few simple heuristics. The proposed algorithm finds high-quality solutions in a fast and intuitively-simple way. In experiments on the COIL database, on the extended COIL database and on the Sonar database of the UCI Irvine repository, DirectSVM is able to find solutions that are similar to these found by the original SVM. However DirectSVM is able to find these solutions substantially faster, while requiring less computational resources than the original SVM.

关键词： Support vector machines Iterative algorithms Neural networks Quadratic programming Pattern recognition Databases Neurons Statistical learning Automatic control Control systems

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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 human interference. However, an autonomous system operating in the real world will often be confronted with previously unseen objects. To solve this problem, we propose a segmentation approach named Automatic Detection And Segmentation (ADAS). For the detection of objects, we use symmetry, one of the Gestalt principles for figure-ground segregation to detect salient objects in a scene. From the initial seed, the object is segmented by iteratively applying graph cuts. We base the segmentation on both 2D and 3D cues: color, depth, and plane information. Instead of using a standard grid-based representation of the image, we use super pixels. Besides being a more natural representation, the use of super pixels greatly improves the processing time of the graph cuts, and provides more noise-robust color and depth information. The results show that both the object-detection as well as the object-segmentation method are successful and outperform existing methods.

关键词： Pixel Image segmentation Image color analysis Robots Databases Object detection Labeling

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Strategies for Object Manipulation using Foveal and Peripheral vision

Strategies for Object Manipulation using Foveal and Peripher...

引用

IEEE International Conference on computer vision Systems (ICVS)

作者： D. Kragic M. Bjorkman Computer Vision and Active Perception Laboratory Royal Institute of Technology Stockholm Sweden

Visual feedback is used extensively in robotics and application areas range from human-robot interaction to object grasping and manipulation. There have been a number of examples of how to develop different components required by the above applications and very few general vision systems capable of performing a variety of tasks. In this paper, we concentrate on vision strategies for robotic manipulation tasks in a domestic environment. In particular, given fetch-and-carry type of tasks, the issues related to the whole detect-approach-grasp loop are considered. We deal with the problem of flexibility and robustness by using monocular and binocular visual cues and their integration. We demonstrate real-time disparity estimation, object recognition and pose estimation. We also show how a combination of foveal and peripheral vision system can be combined in order to provide a wide, low resolution and narrow, high resolution field of view.

关键词： Machine vision computer vision Robot vision systems Object recognition Human robot interaction Visual system Feedback Robustness Robot sensing systems Medical robotics

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