Wörgötter, Florentin Andreas

[["dc.bibliographiccitation.firstpage","5"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","International Journal of Computer Vision"],["dc.bibliographiccitation.lastpage","7"],["dc.bibliographiccitation.volume","72"],["dc.contributor.author","Krüger, Norbert"],["dc.contributor.author","Woergoetter, Florentin"],["dc.contributor.author","van Hulle, Marc M."],["dc.date.accessioned","2017-09-07T11:45:25Z"],["dc.date.available","2017-09-07T11:45:25Z"],["dc.date.issued","2006"],["dc.identifier.doi","10.1007/s11263-006-8889-2"],["dc.identifier.gro","3151771"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8597"],["dc.language.iso","en"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","0920-5691"],["dc.title","Editorial: ECOVISION: Challenges in Early-Cognitive Vision"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dc.type.subtype","editorial_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","293"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Natural Computing"],["dc.bibliographiccitation.lastpage","321"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Woergoetter, Florentin"],["dc.contributor.author","Krüger, Norbert"],["dc.contributor.author","Pugeault, Nicolas"],["dc.contributor.author","Calow, Dirk"],["dc.contributor.author","Lappe, Markus"],["dc.contributor.author","Pauwels, Karl"],["dc.contributor.author","van Hulle, Marc M."],["dc.contributor.author","Tan, Sovira"],["dc.contributor.author","Johnston, Alan"],["dc.date.accessioned","2017-09-07T11:45:29Z"],["dc.date.available","2017-09-07T11:45:29Z"],["dc.date.issued","2004"],["dc.description.abstract","The goal of this review is to discuss different strategies employed by the visual system to limit data-flow and to focus data processing. These strategies can be hard-wired, like the eccentricity-dependent visual resolution or they can be dynamically changing like mechanisms of visual attention. We will ask to what degree such strategies are also useful in a computer vision context. Specifically we will discuss, how to adapt them to technical systems where the substrate for the computations is vastly different from that in the brain. It will become clear that most algorithmic principles, which are employed by natural visual systems, need to be reformulated to better fit to modern computer architectures. In addition, we will try to show that it is possible to employ multiple strategies in parallel to arrive at a flexible and robust computer vision system based on recurrent feedback loops and using information derived from the statistics of natural images."],["dc.identifier.doi","10.1023/b:naco.0000036817.38320.fe"],["dc.identifier.gro","3151779"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8605"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","1567-7818"],["dc.title","Early Cognitive Vision: Using Gestalt-Laws for Task-Dependent, Active Image-Processing"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","81"],["dc.bibliographiccitation.journal","Advances in Imaging and Electron Physics"],["dc.bibliographiccitation.lastpage","146"],["dc.bibliographiccitation.volume","131"],["dc.contributor.author","Krüger, Norbert"],["dc.contributor.author","Wörgötter, Florentin"],["dc.contributor.editor","Hawkes, Peter"],["dc.date.accessioned","2017-09-07T11:45:35Z"],["dc.date.available","2017-09-07T11:45:35Z"],["dc.date.issued","2011"],["dc.description.abstract","This chapter presents the examples of the ambiguities of local visual data in different visual domains, such as line extraction, color, stereo, and local motion. This ambiguity can be resolved by the integration of information based on regularities in visual data. The integration takes place across the temporal and spatial domain, but also across different visual modalities. Natural images represent only a tiny subset of the set of possible images. Indeed, if an image would be produced by a random operator, there are no chances that it would look like something resembling a natural image. The image would look like white noise. Events in one frame can be used to predict events in a second frame, provided some information about the motion is collected. There exist two kinds of regularities: deterministic regularities and statistical regularities. Deterministic regularities allow for deterministic predictions that are in general based on analytically describable geometrical relations grounded on different perspectives of a scene or an object."],["dc.identifier.doi","10.1016/s1076-5670(04)31003-7"],["dc.identifier.gro","3151812"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8642"],["dc.language.iso","en"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.isbn","978-0-12014-773-1"],["dc.relation.issn","1076-5670"],["dc.title","Statistical and Deterministic Regularities: Utilization of Motion and Grouping in Biological and Artificial Visual Systems"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e10663"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","PloS one"],["dc.bibliographiccitation.lastpage","e10663"],["dc.bibliographiccitation.volume","5"],["dc.contributor.author","Pugeault, Nicolas"],["dc.contributor.author","Wörgötter, Florentin"],["dc.contributor.author","Krüger, Norbert"],["dc.date.accessioned","2019-07-09T11:53:16Z"],["dc.date.available","2019-07-09T11:53:16Z"],["dc.date.issued","2010-04-20"],["dc.description.abstract","In its early stages, the visual system suffers from a lot of ambiguity and noise that severely limits the performance of early vision algorithms. This article presents feedback mechanisms between early visual processes, such as perceptual grouping, stereopsis and depth reconstruction, that allow the system to reduce this ambiguity and improve early representation of visual information. In the first part, the article proposes a local perceptual grouping algorithm that - in addition to commonly used geometric information - makes use of a novel multi-modal measure between local edge/line features. The grouping information is then used to: 1\\) disambiguate stereopsis by enforcing that stereo matches preserve groups; and 2\\) correct the reconstruction error due to the image pixel sampling using a linear interpolation over the groups. The integration of mutual feedback between early vision processes is shown to reduce considerably ambiguity and noise without the need for global constraints."],["dc.identifier.doi","10.1371/journal.pone.0010663"],["dc.identifier.fs","580961"],["dc.identifier.pmid","20544006"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/7201"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/60384"],["dc.language.iso","en"],["dc.notes","The work described in this paper was funded by the European projects PACOplus and IRFO. Florentin Woergoetter acknowledges funding by the\r\nBernstein Center for Computational Neuroscience, Göttingen. The funders had no role in study design, data collection and analysis, decision to publish, or\r\npreparation of the manuscript."],["dc.notes.intern","Merged from goescholar"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/027657"],["dc.relation.euproject","PACO-PLUS"],["dc.relation.issn","1932-6203"],["dc.relation.orgunit","Fakultät für Physik"],["dc.rights","CC BY 2.5"],["dc.rights.access","openAccess"],["dc.rights.uri","http://creativecommons.org/licenses/by/2.5/"],["dc.subject.mesh","Algorithms"],["dc.subject.mesh","Humans"],["dc.subject.mesh","Visual Perception"],["dc.title","Disambiguating multi-modal scene representations using perceptual grouping constraints."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","337"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Leonardo"],["dc.bibliographiccitation.lastpage","340"],["dc.bibliographiccitation.volume","38"],["dc.contributor.author","Krüger, Norbert"],["dc.contributor.author","Woergoetter, Florentin"],["dc.date.accessioned","2017-09-07T11:45:31Z"],["dc.date.available","2017-09-07T11:45:31Z"],["dc.date.issued","2005"],["dc.description.abstract","The authors introduce a new kind of computer art motivated by cortical structures in the human visual system. This type of computer art is related to the sub-group of the impressionist art movement called pointillism. However, while pointillism visualizes and makes use of processes that have been associated with the human eye, Symbolic Pointillism also makes cortical processes explicit. The visual representations underlying this art have been developed during a project that aims at the transfer of functional aspects of human vision to artificial systems. The authors have applied their findings in such an artificial vision system and in a sound/vision installation."],["dc.identifier.doi","10.1162/0024094054762052"],["dc.identifier.gro","3151801"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8630"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0024-094X"],["dc.title","Symbolic Pointillism: Computer Art Motivated by Human Brain Structures"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","341"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Network: Computation in Neural Systems"],["dc.bibliographiccitation.lastpage","356"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Kalkan, S."],["dc.contributor.author","Calow, Dirk"],["dc.contributor.author","Woergoetter, Florentin"],["dc.contributor.author","Lappe, M."],["dc.contributor.author","Krüger, Norbert"],["dc.date.accessioned","2017-09-07T11:45:25Z"],["dc.date.available","2017-09-07T11:45:25Z"],["dc.date.issued","2006"],["dc.description.abstract","Different kinds of local image structures (such as homogeneous, edge-like and junction-like patches) can be distinguished by the intrinsic dimensionality of the local signals. Intrinsic dimensionality makes use of variance from a point and a line in spectral representation of the signal in order to classify it as homogeneous, edge-like or junction-like. The concept of intrinsic dimensionality has been mostly exercised using discrete formulations; however, recent work (; ) has introduced a continuous definition. The current study analyzes the distribution of local patches in natural images according to this continuous understanding of intrinsic dimensionality. This distribution reveals specific patterns than can be also associated to local image structures established in computer vision and which can be related to orientation and optic flow features. In particular, we link quantitative and qualitative properties of optic-flow error estimates to these patterns. In this way, we also introduce a new tool for better analysis of optic flow algorithms."],["dc.identifier.doi","10.1080/09548980500445005"],["dc.identifier.gro","3151772"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8598"],["dc.language.iso","en"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","0954-898X"],["dc.title","Local image structures and optic flow estimation"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1179"],["dc.bibliographiccitation.issue","10-11"],["dc.bibliographiccitation.journal","The International Journal of Robotics Research"],["dc.bibliographiccitation.lastpage","1207"],["dc.bibliographiccitation.volume","38"],["dc.contributor.author","Tamosiunaite, Minija"],["dc.contributor.author","Aein, Mohamad Javad"],["dc.contributor.author","Braun, Jan Matthias"],["dc.contributor.author","Kulvicius, Tomas"],["dc.contributor.author","Markievicz, Irena"],["dc.contributor.author","Kapociute-Dzikiene, Jurgita"],["dc.contributor.author","Valteryte, Rita"],["dc.contributor.author","Haidu, Andrei"],["dc.contributor.author","Chrysostomou, Dimitrios"],["dc.contributor.author","Ridge, Barry"],["dc.contributor.author","Krilavicius, Tomas"],["dc.contributor.author","Vitkute-Adzgauskiene, Daiva"],["dc.contributor.author","Beetz, Michael"],["dc.contributor.author","Madsen, Ole"],["dc.contributor.author","Ude, Ales"],["dc.contributor.author","Krüger, Norbert"],["dc.contributor.author","Wörgötter, Florentin"],["dc.date.accessioned","2020-12-10T18:38:25Z"],["dc.date.available","2020-12-10T18:38:25Z"],["dc.date.issued","2019"],["dc.description.abstract","Human beings can generalize from one action to similar ones. Robots cannot do this and progress concerning information transfer between robotic actions is slow. We have designed a system that performs action generalization for manipulation actions in different scenarios. It relies on an action representation for which we perform code-snippet replacement, combining information from different actions to form new ones. The system interprets human instructions via a parser using simplified language. It uses action and object names to index action data tables (ADTs), where execution-relevant information is stored. We have created an ADT database from three different sources (KUKA LWR, UR5, and simulation) and show how a new ADT is generated by cutting and recombining data from existing ADTs. To achieve this, a small set of action templates is used. After parsing a new instruction, index-based searching finds similar ADTs in the database. Then the action template of the new action is matched against the information in the similar ADTs. Code snippets are extracted and ranked according to matching quality. The new ADT is created by concatenating code snippets from best matches. For execution, only coordinate transforms are needed to account for the poses of the objects in the new scene. The system was evaluated, without additional error correction, using 45 unknown objects in 81 new action executions, with 80% success. We then extended the method including more detailed shape information, which further reduced errors. This demonstrates that cut \\u0026 recombine is a viable approach for action generalization in service robotic applications."],["dc.description.sponsorship","European Community’s Seventh Framework Programme FP7 ICT-2011.2.1, Cognitive Systems and Robotics"],["dc.identifier.doi","10.1177/0278364919865594"],["dc.identifier.eissn","1741-3176"],["dc.identifier.issn","0278-3649"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/77309"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.publisher","SAGE Publications"],["dc.relation.eissn","1741-3176"],["dc.relation.issn","0278-3649"],["dc.rights","http://creativecommons.org/licenses/by-nc/4.0/"],["dc.title","Cut & recombine: reuse of robot action components based on simple language instructions"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

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