| 1. |
- Yun, Yixiao, 1987, et al.
(author)
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Maximum-Likelihood Object Tracking from Multi-View Video by Combining Homography and Epipolar Constraints
- 2012
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In: 6th ACM/IEEE Int'l Conf on Distributed Smart Cameras (ICDSC 12), Oct 30 - Nov.2, 2012, Hong Kong. - 9781450317726 ; , s. 6 pages-
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Conference paper (peer-reviewed)abstract
- This paper addresses problem of object tracking in occlusion scenarios, where multiple uncalibrated cameras with overlapping fields of view are used. We propose a novel method where tracking is first done independently for each view and then tracking results are mapped between each pair of views to improve the tracking in individual views, under the assumptions that objects are not occluded in all views and move uprightly on a planar ground which may induce a homography relation between each pair of views. The tracking results are mapped by jointly exploiting the geometric constraints of homography, epipolar and vertical vanishing point. Main contributions of this paper include: (a) formulate a reference model of multi-view object appearance using region covariance for each view; (b) define a likelihood measure based on geodesics on a Riemannian manifold that is consistent with the destination view by mapping both the estimated positions and appearances of tracked object from other views; (c) locate object in each individual view based on maximum likelihood criterion from multi-view estimations of object position. Experiments have been conducted on videos from multiple uncalibrated cameras, where targets experience long-term partial or full occlusions. Comparison with two existing methods and performance evaluations are also made. Test results have shown effectiveness of the proposed method in terms of robustness against tracking drifts caused by occlusions.
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| 2. |
- Gu, Irene Yu-Hua, 1953, et al.
(author)
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Grassmann Manifold Online Learning and Partial Occlusion Handling for Visual Object Tracking under Bayesian Formulation
- 2012
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In: Proceedings - International Conference on Pattern Recognition. - 1051-4651. - 9784990644109 ; , s. 1463-1466
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Conference paper (peer-reviewed)abstract
- This paper addresses issues of online learning and occlusion handling in video object tracking. Although manifold tracking is promising, large pose changes and long term partial occlusions of video objects remain challenging.We propose a novel manifold tracking scheme that tackles such problems, with the following main novelties: (a) Online estimation of object appearances on Grassmann manifolds; (b) Optimal criterion-based occlusion handling during online learning; (c) Nonlinear dynamic model for appearance basis matrix and its velocity; (b) Bayesian formulations separately for the tracking and the online learning process. Two particle filters are employed: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in alternative fashion to mitigate the tracking drift. Experiments on videos have shown robust tracking performance especially when objects contain significantpose changes accompanied with long-term partial occlusions. Evaluations and comparisons with two existing methods provide further support to the proposed method.
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| 3. |
- Dobnik, Simon, 1977
(author)
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Coordinating spatial perspective in discourse
- 2012
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In: Proceedings of the Workshop on Vision and Language 2012 (VL'12): The 2nd Annual Meeting of the EPSRC Network on Vision and Language.
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Conference paper (other academic/artistic)abstract
- We present results of an on-line data collection experiment where we investigate the assignment and coordination of spatial perspective between a pair of dialogue participants situated in a constrained virtual environment.
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| 4. |
- Höglund, Lars, 1946, et al.
(author)
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Maskininlärningsbaserad indexering av digitaliserade museiartefakter - projektrapport
- 2012
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Reports (other academic/artistic)abstract
- Projektet har genomfört försök med maskinbaserad analys och maskininlärning för automatisk indexering och analys av bilder som stöd för registrering av föremål i museibestånd. Resultaten visar att detta är möjligt för avgränsade delmängder i kombination med maskininlärning som stöd för, men inte som ersättning för, manuell analys. Projektet har också funnit behov av utveckling av ett användargränssnitt för både text och bildsökning och utvecklat en prototyplösning för detta, vilket finns dokumenterat i denna rapport och i ett separat appendix till rapporten. Materialet utgör grundunderlag för implementeringar som innebär utökade sökmöjligheter, effektivare registrering samt ett användarvänligt gränssnitt. Arbetet ligger i framkant av forskningsområdets resultat och etablerade metoder och kombinerar statististiska, lingvistiska och datavetenskapliga metoder. Se länk till rapport och även länk till appendix längre ned.
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| 5. |
- Yun, Yixiao, 1987, et al.
(author)
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Image Classification by Multi-Class Boosting of Visual and Infrared Fusion with Applications to Object Pose Recognition
- 2013
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In: Swedish Symposium on Image Analysis (SSBA 2013), March 14-15, Göteborg, Sweden. ; , s. 4-
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Conference paper (other academic/artistic)abstract
- This paper proposes a novel method for multiview object pose classification through sequential learning and sensor fusion. The basic idea is to use images observed in visual and infrared (IR) bands, with the same sampling weight under a multi-class boosting framework. The main contribution of this paper is a multi-class AdaBoost classification framework where visual and infrared information interactively complement each other. This is achieved by learning hypothesis for visual and infrared bands independently and then fusing the optimized hypothesis subensembles. Experiments are conducted on several image datasets including a set of visual and thermal IR images containing 4844 face images in 5 different poses. Results have shown significant increase in classification rate as compared with an existing multi-class AdaBoost algorithm SAMME trained on visual or infrared images alone, as well as a simple baseline classification-fusion algorithm.
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| 6. |
- Kjellin, Andreas, et al.
(author)
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Evaluating 2D and 3D Visualizations of Spatiotemporal Information
- 2010
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In: ACM Transactions on Applied Perception. - : Association for Computing Machinery (ACM). - 1544-3558 .- 1544-3965. ; 7:3, s. 19:1-19:23
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Journal article (peer-reviewed)abstract
- Time-varying geospatial data presents some specific challenges for visualization. Here, we report the results of three experiments aiming at evaluating the relative efficiency of three existing visualization techniques for a class of such data. The class chosen was that of object movement, especially the movements of vehicles in a fictitious landscape. Two different tasks were also chosen. One was to predict where three vehicles will meet in the future given a visualization of their past movement history. The second task was to estimate the order in which four vehicles arrived at a specific place. Our results reveal that previous findings had generalized human perception in these situations and that large differences in user efficiency exist for a given task between different types of visualizations depicting the same data. Furthermore, our results are in line with earlier general findings on the nature of human perception of both object shape and scene changes. Finally, the need for new taxonomies of data and tasks based on results from perception research is discussed.
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| 7. |
- Porathe, Thomas, 1954, et al.
(author)
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Maritime Unmanned Navigation through Intelligence in Networks: The MUNIN project
- 2013
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In: 12th International Conference on Computer and IT Applications in the Maritime Industries, COMPIT’13, Cortona, 15-17 April 2013. - 9783892206637 ; , s. 177-183
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Conference paper (peer-reviewed)abstract
- This paper introduces the MUNIN project attempting to put a 200 meter long bulk carrier under autonomous control. The paper gives a motivation and an overview of the project as well as present some of the key research questions dealing with the human intervention possibilities. As a fallback option the unmanned ship is monitored by a shore control center which has the ability to take direct control if necessary. A challenge for the unmanned ship is the interaction with other manned ships.
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| 8. |
- Linde, Oskar, 1979-, et al.
(author)
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Composed Complex-Cue Histograms : An Investigation of the Information Content in Receptive Field Based Image Descriptors for Object Recognition
- 2012
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In: Computer Vision and Image Understanding. - : Elsevier. - 1077-3142 .- 1090-235X. ; 116:4, s. 538-560
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Journal article (peer-reviewed)abstract
- Recent work has shown that effective methods for recognizing objects and spatio-temporal events can be constructed based on histograms of receptive field like image operations. This paper presents the results of an extensive study of the performance of different types of receptive field like image descriptors for histogram-based object recognition, based on different combinations of image cues in terms of Gaussian derivatives or differential invariants applied to either intensity information, colour-opponent channels or both. A rich set of composed complex-cue image descriptors is introduced and evaluated with respect to the problems of (i) recognizing previously seen object instances from previously unseen views, and (ii) classifying previously unseen objects into visual categories. It is shown that there exist novel histogram descriptors with significantly better recognition performance compared to previously used histogram features within the same class. Specifically, the experiments show that it is possible to obtain more discriminative features by combining lower-dimensional scale-space features into composed complex-cue histograms. Furthermore, different types of image descriptors have different relative advantages with respect to the problems of object instance recognition vs. object category classification. These conclusions are obtained from extensive experimental evaluations on two mutually independent data sets. For the task of recognizing specific object instances, combined histograms of spatial and spatio-chromatic derivatives are highly discriminative, and several image descriptors in terms rotationally invariant (intensity and spatio-chromatic) differential invariants up to order two lead to very high recognition rates. For the task of category classification, primary information is contained in both first- and second-order derivatives, where second-order partial derivatives constitute the most discriminative cue. Dimensionality reduction by principal component analysis and variance normalization prior to training and recognition can in many cases lead to a significant increase in recognition or classification performance. Surprisingly high recognition rates can even be obtained with binary histograms that reveal the polarity of local scale-space features, and which can be expected to be particularly robust to illumination variations. An overall conclusion from this study is that compared to previously used lower-dimensional histograms, the use of composed complex-cue histograms of higher dimensionality reveals the co-variation of multiple cues and enables much better recognition performance, both with regard to the problems of recognizing previously seen objects from novel views and for classifying previously unseen objects into visual categories.
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| 9. |
- Berger, Christian, 1980, et al.
(author)
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Model-based, Composable Simulation for the Development of Autonomous Miniature Vehicles
- 2013
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In: Mod4Sim'13: 3rd International Workshop on Model-driven Approaches for Simulation Engineering at SCS/IEEE Symposium on Theory of Modeling and Simulation in conjunction with SpringSim 2013. - 0735-9276. - 9781627480321 ; 45, s. 118-125
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Conference paper (peer-reviewed)abstract
- Modern vehicles contain nearly 100 embedded control units to realize various comfort and safety functions. These vehicle functions consist of a sensor, a data processing, and an actor layer to react intelligently to stimuli from their context. Recently, these sensors do not only perceive data from the own vehicle but more often also data from the vehicle's surroundings to understand the current traffic situation. Thus, traditional development and testing processes need to be rethought to ensure the required quality especially for safety-critical systems like a collision prevention system. On the example of 1:10 scale model cars, we outline our model-based and composable simulation approach that enabled the virtualized development of autonomous driving capabilities for model cars to compete in an international competition.
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| 10. |
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