| 1. |
- Baldvinsson, Jon R., et al.
(författare)
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IL-GAN : Rare Sample Generation via Incremental Learning in GANs
- 2022
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Ingår i: 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 621-626
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Konferensbidrag (refereegranskat)abstract
- Industry 4.0 imposes strict requirements on the fifth generation of wireless systems (5G), such as high reliability, high availability, and low latency. Guaranteeing such requirements implies that system failures should occur with an extremely low probability. However, some applications (e.g., training a reinforcement learning algorithm to operate in highly reliable systems or rare event simulations) require access to a broad range of observed failures and extreme values, preferably in a short time. In this paper, we propose IL-GAN, an alternative training framework for generative adversarial networks (GANs), which leverages incremental learning (IL) to enable the generation to learn the tail behavior of the distribution using only a few samples. We validate the proposed IL-GAN with data from 5G simulations on a factory automation scenario and real measurements gathered from various video streaming platforms. Our evaluations show that, compared to the state-of-the-art, our solution can significantly improve the learning and generation performance, not only for the tail distribution but also for the rest of the distribution.
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| 2. |
- Bekiroglu, Y., et al.
(författare)
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Visual and tactile 3D point cloud data from real robots for shape modeling and completion
- 2020
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Ingår i: Data in Brief. - : Elsevier. - 2352-3409. ; 30
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Tidskriftsartikel (refereegranskat)abstract
- Representing 3D geometry for different tasks, e.g. rendering and reconstruction, is an important goal in different fields, such as computer graphics, computer vision and robotics. Robotic applications often require perception of object shape information extracted from sensory data that can be noisy and incomplete. This is a challenging task and in order to facilitate analysis of new methods and comparison of different approaches for shape modeling (e.g. surface estimation), completion and exploration, we provide real sensory data acquired from exploring various objects of different complexities. The dataset includes visual and tactile readings in the form of 3D point clouds obtained using two different robot setups that are equipped with visual and tactile sensors. During data collection, the robots touch the experiment objects in a predefined manner at various exploration configurations and gather visual and tactile points in the same coordinate frame based on calibration between the robots and the used cameras. The goal of this exhaustive exploration procedure is to sense unseen parts of the objects which are not visible to the cameras, but can be sensed via tactile sensors activated at touched areas. The data was used for shape completion and modeling via Implicit Surface representation and Gaussian-Process-based regression, in the work “Object shape estimation and modeling, based on sparse Gaussian process implicit surfaces, combining visual data and tactile exploration” [3], and also used partially in “Enhancing visual perception of shape through tactile glances” [4], both studying efficient exploration of objects to reduce number of touches.
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| 3. |
- Bienkiewicz, Marta M. N., et al.
(författare)
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Bridging the gap between emotion and joint action
- 2021
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Ingår i: Neuroscience and Biobehavioral Reviews. - : Elsevier BV. - 0149-7634 .- 1873-7528. ; 131, s. 806-833
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Tidskriftsartikel (refereegranskat)abstract
- Our daily human life is filled with a myriad of joint action moments, be it children playing, adults working together (i.e., team sports), or strangers navigating through a crowd. Joint action brings individuals (and embodiment of their emotions) together, in space and in time. Yet little is known about how individual emotions propagate through embodied presence in a group, and how joint action changes individual emotion. In fact, the multi-agent component is largely missing from neuroscience-based approaches to emotion, and reversely joint action research has not found a way yet to include emotion as one of the key parameters to model socio-motor interaction. In this review, we first identify the gap and then stockpile evidence showing strong entanglement between emotion and acting together from various branches of sciences. We propose an integrative approach to bridge the gap, highlight five research avenues to do so in behavioral neuroscience and digital sciences, and address some of the key challenges in the area faced by modern societies.
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| 4. |
- Björkman, Mårten, 1970-, et al.
(författare)
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Active 3D scene segmentation and detection of unknown objects
- 2010
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Ingår i: IEEE International Conference on Robotics and Automation (ICRA), Anchorage, USA. - : IEEE Robotics and Automation Society. - 9781424450381 ; , s. 3114-3120
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Konferensbidrag (refereegranskat)abstract
- We present an active vision system for segmentationof visual scenes based on integration of several cues. The system serves as a visual front end for generation of object hypotheses for new, previously unseen objects in natural scenes. The system combines a set of foveal and peripheral cameraswhere, through a stereo based fixation process, object hypotheses are generated. In addition to considering the segmentation process in 3D, the main contribution of the paper is integration of different cues in a temporal framework and improvement of initial hypotheses over time.
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| 5. |
- Björkman, Mårten, 1970-, et al.
(författare)
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Active 3D Segmentation through Fixation of Previously Unseen Objects
- 2010
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Ingår i: British Machine Vision Conference (BMVC), Aberystwyth, UK. - : BMVA Press. - 1901725405 ; , s. 119.1-119.11
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Konferensbidrag (refereegranskat)abstract
- We present an approach for active segmentation based on integration of several cues.It serves as a framework for generation of object hypotheses of previously unseen objectsin natural scenes. Using an approximate Expectation-Maximisation method, the appearance,3D shape and size of objects are modelled in an iterative manner, with fixation usedfor unsupervised initialisation. To better cope with situations where an object is hard tosegregate from the surface it is placed on, a flat surface model is added to the typical twohypotheses used in classical figure-ground segmentation. The framework is further extendedto include modelling over time, in order to exploit temporal consistency for bettersegmentation and to facilitate tracking.
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| 6. |
- Björkman, Mårten, 1970-, et al.
(författare)
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Attending, Foveating and Recognizing Objects in Real World Scenes
- 2004
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Ingår i: British Machine Vision Conference (BMVC), London, UK. - : BMVA Press. - 1901725251 ; , s. 227-236
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Konferensbidrag (refereegranskat)abstract
- Recognition in cluttered real world scenes is a challenging problem. To find a particular object of interest within a reasonable time, a wide field of view is preferable. However, as we will show with practical experiments, robust recognition is easier if the object is foveated and subtends a considerable partof the visual field. In this paper a binocular system able to overcome these two conflicting requirements will be presented. The system consists of two sets of cameras, a wide field pair and a foveal one. From disparities a number of object hypotheses are generated. An attentional process based on hue and 3D size guides the foveal cameras towards the most salient regions. With the object foveated and segmented in 3D, recognition is performed using scale invariant features. The system is fully automised and runs at real-time speed.
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| 7. |
- Björkman, Mårten, 1970-, et al.
(författare)
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Detecting, segmenting and tracking unknown objects using multi-label MRF inference
- 2014
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Ingår i: Computer Vision and Image Understanding. - : Elsevier. - 1077-3142 .- 1090-235X. ; 118, s. 111-127
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Tidskriftsartikel (refereegranskat)abstract
- This article presents a unified framework for detecting, segmenting and tracking unknown objects in everyday scenes, allowing for inspection of object hypotheses during interaction over time. A heterogeneous scene representation is proposed, with background regions modeled as a combinations of planar surfaces and uniform clutter, and foreground objects as 3D ellipsoids. Recent energy minimization methods based on loopy belief propagation, tree-reweighted message passing and graph cuts are studied for the purpose of multi-object segmentation and benchmarked in terms of segmentation quality, as well as computational speed and how easily methods can be adapted for parallel processing. One conclusion is that the choice of energy minimization method is less important than the way scenes are modeled. Proximities are more valuable for segmentation than similarity in colors, while the benefit of 3D information is limited. It is also shown through practical experiments that, with implementations on GPUs, multi-object segmentation and tracking using state-of-art MRF inference methods is feasible, despite the computational costs typically associated with such methods.
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| 8. |
- Björkman, Mårten, 1970-, et al.
(författare)
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Enhancing Visual Perception of Shape through Tactile Glances
- 2013
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Ingår i: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on. - : IEEE conference proceedings. - 2153-0866 .- 2153-0858. - 9781467363587 ; , s. 3180-3186
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Konferensbidrag (refereegranskat)abstract
- Object shape information is an important parameter in robot grasping tasks. However, it may be difficult to obtain accurate models of novel objects due to incomplete and noisy sensory measurements. In addition, object shape may change due to frequent interaction with the object (cereal boxes, etc). In this paper, we present a probabilistic approach for learning object models based on visual and tactile perception through physical interaction with an object. Our robot explores unknown objects by touching them strategically at parts that are uncertain in terms of shape. The robot starts by using only visual features to form an initial hypothesis about the object shape, then gradually adds tactile measurements to refine the object model. Our experiments involve ten objects of varying shapes and sizes in a real setup. The results show that our method is capable of choosing a small number of touches to construct object models similar to real object shapes and to determine similarities among acquired models.
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| 9. |
- Björkman, Mårten, 1970-, et al.
(författare)
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Foveated Figure-Ground Segmentation and Its Role in Recognition
- 2005
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Ingår i: BMVC 2005 - Proceedings of the British Machine Vision Conference 2005. - : British Machine Vision Association, BMVA. - 1901725294 - 1901725308 ; , s. 819-828
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Konferensbidrag (refereegranskat)abstract
- Figure-ground segmentation and recognition are two interrelated processes. In this paper we present a method for foveated segmentation and evaluate it in the context of a binocular real-time recognition system. Segmentation is solved as a binary labeling problem using priors derived from the results ofa simplistic disparity method. Doing so we are able to cope with situations when the disparity range is very wide, situations that has rarely been considered, but appear frequently for narrow-field camera sets. Segmentation and recognition are then integrated into a system able to locate, attend to and recognise objects in typical cluttered indoor scenes. Finally, we try to answer two questions: is recognition really helped by segmentation and what is the benefit of multiple cues for recognition?
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| 10. |
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