Publikationer av Tony Lindeberg
Refereegranskade
Artiklar
[1]
Lindeberg, T. (2023). A time-causal and time-recursive scale-covariant scale-space representation of temporal signals and past time. Biological Cybernetics, 117(1-2), 21-59.
[2]
Lindeberg, T. (2023). Covariance properties under natural image transformations for the generalized Gaussian derivative model for visual receptive fields. Frontiers in Computational Neuroscience, 17, 1189949-1-1189949-23.
[3]
Maki, A., Kragic, D., Kjellström, H., Azizpour, H., Sullivan, J., Björkman, M. ... Sundblad, Y. (2022). In Memoriam : Jan-Olof Eklundh. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(9), 4488-4489.
[4]
Lindeberg, T. (2022). Scale-covariant and scale-invariant Gaussian derivative networks. Journal of Mathematical Imaging and Vision, 64(3), 223-242.
[5]
Jansson, Y. & Lindeberg, T. (2022). Scale-invariant scale-channel networks : Deep networks that generalise to previously unseen scales. Journal of Mathematical Imaging and Vision, 64(5), 506-536.
[6]
Lindeberg, T. (2021). Normative theory of visual receptive fields. Heliyon, 7(1), e05897-1-e05897-20.
[7]
Lindeberg, T. (2020). Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade. Journal of Mathematical Imaging and Vision, 62(1), 120-148.
[8]
Lindeberg, T. (2018). Dense scale selection over space, time and space-time. SIAM Journal on Imaging Sciences, 11(1), 407-441.
[9]
Jansson, Y. & Lindeberg, T. (2018). Dynamic texture recognition using time-causal and time-recursive spatio-temporal receptive fields. Journal of Mathematical Imaging and Vision, 60(9), 1369-1398.
[10]
Friberg, A., Lindeberg, T., Hellwagner, M., Helgason, P., Salomão, G. L., Elowsson, A. ... Ternström, S. (2018). Prediction of three articulatory categories in vocal sound imitations using models for auditory receptive fields. Journal of the Acoustical Society of America, 144(3), 1467-1483.
[11]
Lindeberg, T. (2018). Spatio-temporal scale selection in video data. Journal of Mathematical Imaging and Vision, 60(4), 525-562.
[12]
Lindeberg, T. (2017). Temporal scale selection in time-causal scale space. Journal of Mathematical Imaging and Vision, 58(1), 57-101.
[13]
Lindeberg, T. (2016). Time-causal and time-recursive spatio-temporal receptive fields. Journal of Mathematical Imaging and Vision, 55(1), 50-88.
[14]
Lindeberg, T. & Friberg, A. (2015). Idealized computational models for auditory receptive fields. PLOS ONE, 10(3).
[15]
Lindeberg, T. (2015). Image matching using generalized scale-space interest points. Journal of Mathematical Imaging and Vision, 52(1), 3-36.
[16]
Lindeberg, T. (2013). A computational theory of visual receptive fields. Biological Cybernetics, 107(6), 589-635.
[17]
Lindeberg, T. (2013). Invariance of visual operations at the level of receptive fields. PLOS ONE, 8(7), e66990-1-e66990-33.
[18]
Lindeberg, T. (2013). Scale Selection Properties of Generalized Scale-Space Interest Point Detectors. Journal of Mathematical Imaging and Vision, 46(2), 177-210.
[19]
Linde, O. & Lindeberg, T. (2012). Composed Complex-Cue Histograms : An Investigation of the Information Content in Receptive Field Based Image Descriptors for Object Recognition. Computer Vision and Image Understanding, 116(4), 538-560.
[20]
Lindeberg, T. (2011). Generalized Gaussian Scale-Space Axiomatics Comprising Linear Scale-Space, Affine Scale-Space and Spatio-Temporal Scale-Space. Journal of Mathematical Imaging and Vision, 40(1), 36-81.
[21]
Laptev, I., Caputo, B., Schüldt, C. & Lindeberg, T. (2007). Local velocity-adapted motion events for spatio-temporal recognition. Computer Vision and Image Understanding, 108(3), 207-229.
[22]
Laptev, I. & Lindeberg, T. (2004). Velocity adaptation of spatio-temporal receptive fields for direct recognition of activities : an experimental study. Image and Vision Computing, 22(2), 105-116.
[23]
Laptev, I. & Lindeberg, T. (2003). A Distance Measure and a Feature Likelihood Map Concept for Scale-Invariant Model Matching. International Journal of Computer Vision, 52(2), 97-120.
[24]
Roland, P., Svensson, G., Lindeberg, T., Risch, T., Baumann, P., Dehmel, A. ... Zilles, K. (2001). A database generator for human brain imaging. TINS - Trends in Neurosciences, 24(10), 562-564.
[25]
Rosbacke, M., Lindeberg, T., Björkman, E. & Roland, P. E. (2001). Evaluation of using absolute versus relative base level when analyzing brain activation images using the scale-space primal sketch. Medical Image Analysis, 5(2), 89-110.
[26]
Wiltschi, K., Pinz, A. & Lindeberg, T. (2000). An automatic assessment scheme for steel quality inspection. Machine Vision and Applications, 12(3), 113-128.
[27]
Laptev, I., Mayer, H., Lindeberg, T., Eckstein, W., Steger, C. & Baumgartner, A. (2000). Automatic extraction of roads from aerial images based on scale space and snakes. Machine Vision and Applications, 12(1), 23-31.
[28]
Almansa, A. & Lindeberg, T. (2000). Fingerprint enhancement by shape adaptation of scale-space operators with automatic scale selection. IEEE Transactions on Image Processing, 9(12), 2027-2042.
[29]
Bretzner, L. & Lindeberg, T. (2000). Qualitative Multi-Scale Feature Hierarchies for Object Tracking. Journal of Visual Communication and Image Representation, 11, 115-129.
[30]
Lindeberg, T., Lidberg, P. & Roland, P. (1999). Analysis of brain activation patterns using a 3-D scale-space primal sketch. Human Brain Mapping, 7(3), 166-94.
[31]
Lindeberg, T. (1998). A scale selection principle for estimating image deformations. Image and Vision Computing, 16, 961-977.
[32]
Lindeberg, T. (1998). Edge detection and ridge detection with automatic scale selection. International Journal of Computer Vision, 30(2), 117-154.
[33]
Bretzner, L. & Lindeberg, T. (1998). Feature Tracking with Automatic Selection of Spatial Scales. Computer Vision and Image Understanding, 71(3), 385-393.
[34]
Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79-116.
[35]
Lindeberg, T. & Li, M.-X. (1997). Segmentation and classification of edges using minimum description length approximation and complementary junction cues. Computer Vision and Image Understanding, 67(1), 88-98.
[36]
Lindeberg, T. & Gårding, J. (1997). Shape-adapted smoothing in estimation of 3-D depth cues from affine distortions of local 2-D brightness structure. Image and Vision Computing, 15(6), 415-434.
[37]
Gårding, J. & Lindeberg, T. (1996). Direct computation of shape cues using scale-adapted spatial derivative operators. International Journal of Computer Vision, 17(2), 163-191.
[38]
Lindeberg, T. (1994). Scale-Space Theory : A Basic Tool for Analysing Structures at Different Scales. Journal of Applied Statistics, 21, 225-270.
[39]
Lindeberg, T. (1993). Detecting salient blob-like image structures and their scales with a scale-space primal sketch: A method for focus-of-attention. International Journal of Computer Vision, 11(3), 283-318.
[40]
Lindeberg, T. (1993). Discrete Derivative Approximations with Scale-Space Properties : A Basis for Low-Level Feature Extraction. Journal of Mathematical Imaging and Vision, 3(4), 349-376.
[41]
Lindeberg, T. (1993). Effective Scale : A Natural Unit for Measuring Scale-Space Lifetime. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(10), 1068-1074.
[42]
Lindeberg, T. (1992). Scale-Space Behaviour of Local Extrema and Blobs. J. of Mathematical Imaging and Vision, 1, 65-99.
[43]
Lindeberg, T. & Eklundh, J.-O. (1992). The Scale-Space Primal Sketch: Construction and Experiments. Image and Vision Computing, 10(1), 3-18.
[44]
Lindeberg, T. & Eklundh, J.-O. (1991). Analysis of aerosol images using the scale-space primal sketch. Machine Vision and Applications, 4(3), 135-144.
[45]
Lindeberg, T. & Eklundh, J.-O. (1991). On the Computation of a Scale-Space Primal Sketch. Journal of Visual Communication and Image Representation, 2(1), 55-78.
[46]
Brunnström, K., Eklundh, J.-O. & Lindeberg, T. (1990). Scale and Resolution in Active Analysis of Local Image Structure. Image and Vision Computing, 8, 289-296.
[47]
Lindeberg, T. (1990). Scale-space for discrete signals. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(3), 234-254.
Konferensbidrag
[48]
Jansson, Y., Lindeberg, T. (2021). Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges. I ICPR 2020: International Conference on Pattern Recognition. (s. 1181-1188). Institute of Electrical and Electronics Engineers (IEEE).
[49]
Lindeberg, T. (2021). Scale-covariant and scale-invariant Gaussian derivative networks. I Scale Space and Variational Methods in Computer Vision. (s. 3-14). Springer Nature.
[50]
Finnveden, L., Jansson, Y., Lindeberg, T. (2021). Understanding when spatial transformer networks do not support invariance, and what to do about it. I ICPR 2020: International Conference on Pattern Recognition. (s. 3427-3434). Institute of Electrical and Electronics Engineers (IEEE).
[51]
Jansson, Y., Maydanskiy, M., Finnveden, L., Lindeberg, T. (2020). Spatial transformations in convolutional networks and invariant recognition. Presenterad vid DeepMath2020 Conference on the Mathematical Theory of Deep Neural Networks Nov 5 - Nov 6, 2020.
[52]
Lindeberg, T. (2019). Provably scale-covariant networks from oriented quasi quadrature measures in cascade. I Scale Space and Variational Methods in Computer Vision. (s. 328-340). Springer Berlin/Heidelberg.
[53]
Jansson, Y., Lindeberg, T. (2017). Dynamic texture recognition using time-causal spatio-temporal scale-space filters. I Scale Space and Variational Methods in Computer Vision. (s. 16-28). Springer.
[54]
Lindeberg, T. (2017). Spatio-temporal scale selection in video data. I Scale Space and Variational Methods in Computer Vision. (s. 3-15). Springer-Verlag Tokyo Inc.
[55]
Lindeberg, T., Friberg, A. (2015). Scale-space theory for auditory signals. I Scale Space and Variational Methods in Computer Vision: 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings. (s. 3-15). Springer.
[56]
Lindeberg, T. (2015). Separable time-causal and time-recursive spatio-temporal receptive fields. I Scale Space and Variational Methods in Computer Vision: 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings. (s. 90-102). Springer.
[57]
Lindeberg, T. (2013). Image matching using generalized scale-space interest points. I Scale Space and Variational Methods in Computer Vision: 4th International Conference, SSVM 2013, Schloss Seggau, Leibnitz, Austria, , June 2-6, 2013, Proceedings. (s. 355-367). Springer Berlin/Heidelberg.
[58]
Lindeberg, T. (2013). Invariance of visual operations at the level of receptive fields. Presenterad vid CNS 2013: 22nd Annual Computational Neuroscience Meeting, July 13-18, Paris, France. BMC Neuroscience 14(Suppl 1). (s. P242).
[59]
Laptev, I., Lindeberg, T. (2006). Local descriptors for spatio-temporal recognition. I Spatial Coherence For Visual Motion Analysis: First International Workshop, SCVMA 2004, Prague, Czech Republic, May 15, 2004. Revised Papers. (s. 91-103). Springer Berlin/Heidelberg.
[60]
Lindeberg, T., Akbarzadeh, A., Laptev, I. (2004). Galilean-diagonalized spatio-temporal interest operators. I Proc. 17th International Conference on Pattern Recognition (ICPR). (s. 57-62).
[61]
Linde, O., Lindeberg, T. (2004). Object recognition using composed receptive field histograms of higher dimensionality. I Proceedings of the 17th International Conference on Pattern Recognition. (s. 1-6). IEEE conference proceedings.
[62]
Laptev, I., Lindeberg, T. (2004). Velocity adaptation of space-time interest points. I Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. (s. 52-56). IEEE conference proceedings.
[63]
Undeman, C., Lindeberg, T. (2003). Fully Automatic Segmentation of MRI Brain Images using Probabilistic Anisotropic Diffusion and Multi-Scale Watersheds. I Scale Space'03 Proceedings of the 4th International Conference on Scale space methods in computer vision. (s. 641-656). Springer Berlin/Heidelberg.
[64]
Laptev, I., Lindeberg, T. (2003). Interest point detection and scale selection in space-time. I Scale Space Methods in Computer Vision: 4th International Conference, Scale Space 2003 Isle of Skye, UK, June 10–12, 2003 Proceedings. (s. 372-387). Springer Berlin/Heidelberg.
[65]
Lindeberg, T., Bretzner, L. (2003). Real-time scale selection in hybrid multi-scale representations. I Proc. Scale-Space’03. (s. 148-163). Springer Berlin/Heidelberg.
[66]
Laptev, I., Lindeberg, T. (2003). Space-time interest points. I Proceedings of Ninth IEEE International Conference on Computer Vision, 2003: ICCV'03. (s. 432-439). IEEE conference proceedings.
[67]
Bretzner, L., Laptev, I., Lindeberg, T. (2002). Hand-gesture recognition using multi-scale colour features, hierarchical features and particle filtering. I Fifth IEEE International Conference on Automatic Face and Gesture Recognition, 2002. Proceedings. (s. 63-74). IEEE conference proceedings.
[68]
Shokoufandeh, A., Dickinson, S., Jönsson, C., Bretzner, L., Lindeberg, T. (2002). On the Representation and Matching of Qualitative Shape at Multiple Scales. I Computer Vision — ECCV 2002: 7th European Conference on Computer Vision Copenhagen, Denmark, May 28–31, 2002 Proceedings, Part III. (s. 759-775). Springer Berlin/Heidelberg.
[69]
Lindeberg, T. (2002). Time-recursive velocity-adapted spatio-temporal scale-space filters. Presenterad vid 7th European Conference on Computer Vision. (s. 52-67).
[70]
Laptev, I., Lindeberg, T. (2002). Velocity-adapted spatio-temporal receptive fields for direct recognition of activities. I Proc. ECCV’02 Workshop on Statistical Methods in Video Processing. (s. 61-66).
[71]
Laptev, I., Lindeberg, T. (2001). A multi-scale feature likelihood map for direct evaluation of object hypotheses. I Proc Scale-Space and Morphology in Computer Vision. (s. 98-110). Springer Berlin/Heidelberg.
[72]
Laptev, I., Lindeberg, T. (2001). Tracking of multi-state hand models using particle filtering and a hierarchy of multi-scale image features. I Scale-Space and Morphology in Computer Vision: Third International Conference, Scale-Space 2001 Vancouver, Canada, July 7–8, 2001 Proceedings. (s. 63-74). Springer Berlin/Heidelberg.
[73]
Björkman, E., Zagal, J. C., Lindeberg, T., Roland, P. E. (2000). Evaluation of design options for the scale-space primal sketch analysis of brain activation images. Presenterad vid Sixth Annual Meeting of the Organization For Human Brain Mapping. (s. 656-656).
[74]
Zagal, J. C., Björkman, E., Lindeberg, T., Roland, P. (2000). Signficance determination for the scale-space primal sketch by comparison of statistics of scale-space blob volumes computed from PET signals vs. residual noise. Presenterad vid Sixth Annual Meeting of the Organization For Human Brain Mapping. (s. 493-493).
[75]
Lindeberg, T. (1999). Automatic scale selection as a pre-processing stage for interpreting the visual world. I Proc. Fundamental StructuralProperties in Image and Pattern Analysis FSPIPA'99 , (Budapest, Hungary), September 6-7, 1999. (s. 9-23). Österreichischen Computer Gesellschaft.
[76]
Bretzner, L., Lindeberg, T. (1999). Qualitative multi-scale feature hierarchies for object tracking. I Proc Scale-Space Theories in Computer Vision Med. (s. 117-128). Elsevier.
[77]
Bretzner, L., Lindeberg, T. (1998). Use your hand as a 3-D mouse or relative orientation from extended sequences of sparse point and line correspondances using the affine trifocal tensor. I Computer Vision — ECCV'98: 5th European Conference on Computer Vision Freiburg, Germany, June, 2–6, 1998 Proceedings, Volume I. (s. 141-157). Springer Berlin/Heidelberg.
[78]
Lindeberg, T., Lidberg, P., Roland, P. (1997). Analysis of Brain Activation Patterns Using A 3-D Scale-Space Primal Sketch. Presenterad vid 3rd International Conference on Functional Mapping of the Human Brain,. (s. 393-393).
[79]
Lindeberg, T., Eriksson, B., Johansson, F., Roland, P. (1997). Automatic matching of brain images and brain atlases using multi-scale fusion algorithms. Presenterad vid 3rd International Conference on Functional Mapping of the Human Brain: HMB'97.
[80]
Wiltschi, K., Pinz, A., Lindeberg, T. (1997). Classification of Carbide Distributions using Scale Selection and Directional Distributions. I Proc. 4th International Conference on Image Processing: ICIP'97. (s. 122-125).
[81]
Lindeberg, T. (1997). Linear spatio-temporal scale-space. I Scale-Space Theory in Computer Vision: Proceedings of First International Conference, Scale-Space'97 Utrecht, The Netherlands, July 2–4, 1997. (s. 113-127). Springer Berlin/Heidelberg.
[82]
Lindeberg, T. (1997). On Automatic Selection of Temporal Scales in Time-Casual Scale-Space. I Proceedings of the Algebraic Frames for the Perception-Action Cycle: AFPAC'97 (Kiel, Germany). (s. 94-113).
[83]
Bretzner, L., Lindeberg, T. (1997). On the handling of spatial and temporal scales in feature tracking. I Scale-Space Theory in Computer Vision: First International Conference, Scale-Space'97 Utrecht, The Netherlands, July 2–4, 1997 Proceedings. (s. 128-139). Springer Berlin/Heidelberg.
[84]
Lindeberg, T. (1996). Edge detection and ridge detection with automatic scale selection. I Proc Computer Vision and Pattern Recognition (CPR’96). (s. 465-470).
[85]
Lindeberg, T. (1996). Scale-space theory : A framework for handling image structures at multiple scales. I Proc. CERN School of Computing, Egmond aan Zee, The Netherlands, 8–21 September, 1996. (s. 27-38).
[86]
Lindeberg, T., Fagerström, D. (1996). Scale-space with causal time direction. Presenterad vid 4th European Conference on Computer Vision, (Cambridge, England), April 14-18, 1996. (s. 229-240). Berlin / Heidelberg: Springer.
[87]
Åkerman, S., Lindeberg, T., Roland, P. (1996). Surface Model Generation and Segmentation of the Human Celebral Cortex for the Construction of Unfolded Cortical Maps. I Proc. 2nd International Conference on Functional Mapping of the Human Brain: HBM'96, published in Neuroimage, volume 3, number 3. (s. S126-S126).
[88]
Lindeberg, T., Li, M.-X. (1995). Automatic generation of break points for MDL based curve classification. I Scandinavian Conference on Image Analysis: SCIA'95. (s. 767-776).
[89]
Lindeberg, T. (1995). Direct estimation of affine image deformations using visual front-end operations with automatic scale selection. I Proc. 5th International Conference on Computer Vision: ICCV'95 (Boston, MA). (s. 134-141). IEEE Computer Society.
[90]
Gårding, J., Lindeberg, T. (1994). Direct estimation of local surface shape in a fixating binocular vision system. I Computer Vision — ECCV '94: Third European Conference on Computer Vision Stockholm, Sweden, May 2–6, 1994 Proceedings, Volume I. (s. 365-376). Springer Berlin/Heidelberg.
[91]
Lindeberg, T. (1994). Junction detection with automatic selection of detection scales and localization scales. I Proc. 1st International Conference on Image Processing: ICIP'94 (Austin, Texas). (s. I:924-928).
[92]
Lindeberg, T., Gårding, J. (1994). Shape-Adapted Smoothing in Estimation of 3-D Depth Cues from Affine Distortions of Local 2-D Brightness Structure. I Computer Vision — ECCV '94: Third European Conference on Computer Vision Stockholm, Sweden, May 2–6, 1994 Proceedings, Volume I. (s. 389-400).
[93]
Lindeberg, T. (1993). On scale selection for differential operators. I Proc. 8th Scandinavian Conference on Image Analysis, (Troms, Norway), May 1993,: SCIA'93. (s. 857-866).
[94]
Lindeberg, T., Gårding, J. (1993). Shape from Texture from a Multi-Scale Perspective. I Fourth International Conference on Computer Vision, 1993. Proceedings: ICCV'93. (s. 683-691). IEEE conference proceedings.
[95]
Brunnström, K., Lindeberg, T., Eklundh, J.-O. (1992). Active detection and classification of junctions by foveation with a head-eye system guided by the scale-space primal sketch. I Computer Vision — ECCV'92: Second European Conference on Computer Vision Santa Margherita Ligure, Italy, May 19–22, 1992 Proceedings. (s. 701-709). Springer Berlin/Heidelberg.
[96]
Lindeberg, T. (1992). Scale-Space Behaviour and Invariance Properties of Differential Singularities. I Shape inPicture: Mathematical Description of Shape in Grey-Level Images: Proc. of Workshop in Driebergen, Netherlands, Sep. 7--11, 1992. (s. 591-600). Springer.
[97]
Lindeberg, T. (1992). Scale-Space for N-dimensional discrete signals. I Shape inPicture: Mathematical Description of Shape in Grey-Level Images: Proc. of Workshop in Driebergen, Netherlands, Sep. 7--11, 1992. (s. 571-590). Springer.
[98]
Lindeberg, T. (1991). On the behaviour in scale-space of local extrema and blobs. I Scandinavian Conference on Image Analysis: SCIA'91 (Aalborg, Denmark). (s. 8-17).
[99]
Lindeberg, T., Eklundh, J.-O. (1990). Construction of a Scale-Space Primal Sketch. I Proceedings of the British Machine Vision Conference 1990: BMVC'90 (Oxford, England). (s. 97-102). The British Machine Vision Association and Society for Pattern Recognition.
[100]
Brunnström, K., Eklundh, J.-O., Lindeberg, T. (1990). On Scale and Resolution in the Analysis of Local Image Structure. I Proc. 1st European Conf. on Computer Vision. (s. 3-12).
[101]
Lindeberg, T., Eklundh, J.-O. (1990). Scale detection and region extraction from a scale-space primal sketch. I Computer Vision, 1990. Proceedings, Third International Conference on. (s. 416-426). IEEE Computer Society.
[102]
Lindeberg, T. (1989). Scale-space for discrete images. I Scandinavian Conference on Image Analysis: SCIA'89 (Oulo, Finland). (s. 1098-1107).
Kapitel i böcker
[103]
Lindeberg, T. (2021). Scale selection. I Katsushi Ikeuchi (Editor-in-Chief) (Red.), Computer Vision ( (2 uppl.) s. 1-14). Springer.
[104]
Lindeberg, T. (2014). Scale selection. I Katsushi Ikeuchi (Red.), Computer Vision: A Reference Guide (s. 701-713). Springer US.
[105]
Lindeberg, T. (2013). Generalized axiomatic scale-space theory. I P. Hawkes (Red.), Advances in Imaging and Electron Physics, Vol 178 (s. 1-96). Elsevier.
[106]
Lindeberg, T. (2009). Scale-Space. I Benjamin Wah (Red.), Wiley Encyclopedia of Computer Science and Engineering (s. 2495-2504). Hoboken, New Jersey: John Wiley & Sons.
[107]
Lindeberg, T. (2001). Corner detection. I Michiel Hazewinkel (Red.), Encyclopaedia of Mathematics. Springer.
[108]
Lindeberg, T. (2001). Edge detection. I Michiel Hazewinkel (Red.), Encyclopaedia of Mathematics. Springer.
[109]
Lindeberg, T. (2001). Scale-space theory. I Michiel Hazewinkel (Red.), Encyclopaedia of Mathematics. Springer.
[110]
Almansa, A. & Lindeberg, T. (1996). Enhancement of Fingerprint Images by Shape-Adapted Scale-Space Operators. I J. Sporring, M. Nielsen, L. Florack, and P. Johansen (Red.), Gaussian Scale-Space Theory. Part I: Proceedings of PhD School on Scale-Space Theory (Copenhagen, Denmark) May 1996 (s. 21-30). Springer Science+Business Media B.V.
[111]
Lindeberg, T. (1996). On the axiomatic foundations of linear scale-space : Combining semi-group structure with causality vs. scale invariance. I J. Sporring, M. Nielsen, L. Florack and P. Johansen (Red.), Gaussian Scale-Space Theory: Proceedings of PhD School on Scale-Space (Copenhagen, Denmark) May 1996. Kluwer Academic Publishers.
[112]
Lindeberg, T. & Li, M.-X. (1995). Segmentation and classification of edges using minimum description length approximation and complementary junction cues. I Gunilla Borgefors (Red.), Theory and Applications of Image Analysis II: Selected Papers from the 9th Scandinavian Conference on Image Analysis, Uppsala, Sweden, 1995. World Scientific.
[113]
Lindeberg, T. (1991). On the behaviour in scale-space of local extrema and blobs. I P. Johansen and S. Olsen (Red.), Theory and Applications of Image Analysis: Selected Papers from the 7th Scandinavian Conference on Image Analysis (Aalborg, Denmark, 1991) (s. 38-47). World Scientific.
Övriga
[114]
Icke refereegranskade
Konferensbidrag
[115]
Finnveden, L., Jansson, Y., Lindeberg, T. (2020). The problems with using STNs to align CNN feature maps. Presenterad vid Northern Lights Deep Learning Workshop 2020, Tromsø, Norway, 20-21 Jan 2020.
[116]
Lindeberg, T. (2016). Time-causal and time-recursive receptive fields for invariance and covariance under natural image transformations. Presenterad vid First European Machine Vision Forum, Heidelberg, Germany, September 8-9, 2016..
[117]
Lindeberg, T. (2016). Time-causal and time-recursive spatio-temporal receptive fields for computer vision and computational modelling of biological vision. I International Workshop on Geometry, PDE’s and Lie Groups in Image Analysis, Eindhoven, The Netherlands, August 24-26, 2016...
[118]
Lindeberg, T. (2013). A framework for invariant visual operations based on receptive field responses. I SSVM 2013: Fourth International Conference on Scale Space and Variational Methods in Computer Vision, June 2-6, Schloss Seggau, Graz region, Austria: Invited keynote address..
[119]
Lindeberg, T. (1996). Automatic Scale Selection as a Pre-Processing Stage to Interpreting Real-World Data. I Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence (Toulouse, France): Invited keynote address. (s. 490-490).
Böcker
[120]
Kapitel i böcker
[121]
Lindeberg, T. (1999). Principles for Automatic Scale Selection. I Berndt Jähne (Red.), Handbook on Computer Vision and Applications: volume II (s. 239-274). Academic Press.
[122]
Lindeberg, T. & ter Haar Romeny, B. (1994). Linear Scale-Space I : Basic Theory. I Geometry-Driven Diffusion in Computer Vision (s. 1-41). Kluwer Academic Publishers.
[123]
Lindeberg, T. & ter Haar Romeny, B. (1994). Linear Scale-Space II : Early visual operations. I Geometry-Driven Diffusion in Vision (s. 43-77). Kluwer Academic Publishers.
Avhandlingar
[124]
Lindeberg, T. (1991). Discrete Scale-Space Theory and the Scale-Space Primal Sketch (Doktorsavhandling , KTH Royal Institute of Technology, Stockholm, ISRN KTH/NA/P 91/8). Hämtad från http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-58570.
Rapporter
[125]
[126]
[127]
[128]
[129]
[130]
[131]
[132]
Lindeberg, T. (2023). Orientation selectivity of affine Gaussian derivative based receptive fields. .
[133]
[134]
Jansson, Y. & Lindeberg, T. (2021). Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales. .
[135]
Jansson, Y. & Lindeberg, T. (2020). Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges. .
[136]
Jansson, Y., Maydanskiy, M., Finnveden, L. & Lindeberg, T. (2020). Inability of spatial transformations of CNN feature maps to support invariant recognition. .
[137]
[138]
Finnveden, L., Jansson, Y. & Lindeberg, T. (2020). Understanding when spatial transformer networks do not support invariance, and what to do about it. .
[139]
[140]
Lindeberg, T. (2017). Discrete approximations of the affine Gaussian derivative model for visual receptive fields. KTH Royal Institute of Technology.
[141]
Jansson, Y. & Lindeberg, T. (2017). Dynamic texture recognition using time-causal and time-recursive spatio-temporal receptive fields. .
[142]
[143]
[144]
Lindeberg, T., Akbarzadeh, A. & Laptev, I. (2004). Galilean-corrected spatio-temporal interest operators. Dept. of Numerical Analysis and Computer Science.
[145]
Laptev, I. & Lindeberg, T. (2003). A distance measure and a feature likelihood map concept for scale-invariant model matching. .
[146]
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