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Michal Haindl
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- affiliation: Czech Academy of Sciences, Prague, Czech Republic
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2020 – today
- 2024
- [j25]Pavel Vácha, Michal Haindl:
Texture recognition under scale and illumination variations. J. Inf. Telecommun. 8(1): 130-148 (2024) - 2023
- [c114]Stanislav Mikes, Michal Haindl:
Optimal Activation Function for Anisotropic BRDF Modeling. VISIGRAPP (1: GRAPP) 2023: 162-169 - [c113]Michal Haindl, Nahidbanu Shaikh:
Texture Quality Criteria Comparison. ICASSP Workshops 2023: 1-5 - [c112]Pavel Zid, Michal Haindl, Vojtech Havlícek:
Governmental Anti-Covid Measures Effectiveness Detection. KES 2023: 2922-2931 - [c111]Pavel Kríz, Michal Haindl:
Multispectral Texture Benchmark. KES 2023: 3143-3152 - [c110]Michal Haindl:
Survival Modeling of Disease Consequences and Post-disease Syndromes. MICAD 2023: 365-374 - 2022
- [j24]Stanislav Mikes, Michal Haindl:
Texture Segmentation Benchmark. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5647-5663 (2022) - [c109]Michal Haindl, Votech Havlícek:
BRDF Anisotropy Criterion. ACIIDS (2) 2022: 434-444 - [c108]Pavel Vácha, Michal Haindl:
Textural Features Sensitivity to Scale and Illumination Variations. ICCCI (CCIS Volume) 2022: 237-249 - [c107]Michal Haindl, Pavel Zid:
Melanoma Recognition. VISIGRAPP (4: VISAPP) 2022: 722-729 - 2021
- [c106]Michal Havlícek, Michal Haindl:
Optimized Texture Spectral Similarity Criteria. ICCCI (CCIS Volume) 2021: 644-655 - [c105]Anna Moudrá, Michal Haindl:
Underground Archeological Structures Detection. ICCCI (CCIS Volume) 2021: 690-702 - 2020
- [c104]Michal Haindl, Vojtech Havlícek:
Transfer Learning of Mixture Texture Models. ICCCI 2020: 825-837
2010 – 2019
- 2019
- [j23]Michal Havlícek, Michal Haindl:
Texture spectral similarity criteria. IET Image Process. 13(11): 1998-2007 (2019) - [j22]Michal Haindl, Václav Remes:
Pseudocolor enhancement of mammogram texture abnormalities. Mach. Vis. Appl. 30(4): 785-794 (2019) - [j21]Václav Remes, Michal Haindl:
Bark recognition using novel rotationally invariant multispectral textural features. Pattern Recognit. Lett. 125: 612-617 (2019) - [c103]Michal Haindl, Vojtech Havlícek:
3D Multi-frequency Fully Correlated Causal Random Field Texture Model. ACPR (2) 2019: 423-434 - [c102]Stanislav Mikes, Michal Haindl:
View Dependent Surface Material Recognition. ISVC (1) 2019: 156-167 - [c101]Michal Haindl, Michal Havlícek:
Mutual Information-Based Texture Spectral Similarity Criterion. ISVC (1) 2019: 302-314 - [c100]Michal Haindl, Pavel Zid:
Coniferous Trees Needles-Based Taxonomy Classification. IVCNZ 2019: 1-6 - 2018
- [j20]Václav Remes, Michal Haindl:
Region of interest contrast measures. Kybernetika 54(5): 978-990 (2018) - [j19]Jirí Filip, Martina Kolafová, Michal Havlícek, Radomír Vávra, Michal Haindl, Holly E. Rushmeier:
Evaluating physical and rendered material appearance. Vis. Comput. 34(6-8): 805-816 (2018) - [c99]Radek Richtr, Michal Haindl:
Dynamic Texture Similarity Criterion. ICPR 2018: 904-909 - [c98]Michal Haindl, Vojtech Havlícek:
BTF Compound Texture Model with Non- Parametric Control Field. ICPR 2018: 1151-1156 - [c97]Michal Haindl, Vojtech Havlícek:
BTF Compound Texture Model with Fast Iterative Non-parametric Control Field Synthesis. SITIS 2018: 98-105 - [c96]Michal Haindl, Milos Kudelka:
Multispectral Texture Fidelity Measure. SITIS 2018: 658-663 - [c95]Václav Remes, Michal Haindl:
Rotationally Invariant Bark Recognition. S+SSPR 2018: 22-31 - 2016
- [j18]Michal Haindl, Stanislav Mikes:
A competition in unsupervised color image segmentation. Pattern Recognit. 57: 136-151 (2016) - [c94]Michal Haindl, Vojtech Havlícek:
Two Compound Random Field Texture Models. CIARP 2016: 44-51 - [c93]Matej Sedlácek, Michal Haindl, Dominika Formanová:
An Automatic Tortoise Specimen Recognition. CIARP 2016: 52-59 - [c92]Michal Haindl, Pavel Vácha:
Scale Sensitivity of Textural Features. CIARP 2016: 84-92 - [c91]Milos Kudelka Jr., Michal Haindl:
Texture fidelity criterion. ICIP 2016: 2062-2066 - [c90]Michal Haindl, Vojtech Havlícek:
Three-dimensional Gaussian mixture texture model. ICPR 2016: 2025-2030 - [c89]Mineichi Kudo, Keigo Kimura, Michal Haindl, Hiroshi Tenmoto:
Simultaneous visualization of samples, features and multi-labels. ICPR 2016: 3603-3608 - [c88]Michal Haindl, Michal Havlícek:
A Compound Moving Average Bidirectional Texture Function Model. MISSI 2016: 89-98 - [c87]Michal Haindl, Matej Sedlácek:
Virtual reconstruction of cultural heritage artifacts. IWCIM 2016: 1-5 - 2015
- [j17]Michal Haindl, Mikulás Krupicka:
Unsupervised detection of non-iris occlusions. Pattern Recognit. Lett. 57: 60-65 (2015) - [j16]Stanislav Mikes, Michal Haindl, Giuseppe Scarpa, Raffaele Gaetano:
Benchmarking of Remote Sensing Segmentation Methods. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 8(5): 2240-2248 (2015) - [c86]Michal Haindl, Stanislav Mikes, Mineichi Kudo:
Unsupervised Surface Reflectance Field Multi-segmenter. CAIP (1) 2015: 261-273 - [c85]Michal Haindl, Pavel Vácha:
Wood Veneer Species Recognition Using Markovian Textural Features. CAIP (1) 2015: 300-311 - [c84]Michal Haindl, Václav Remes, Vojtech Havlícek:
BTF Potts compound texture model. Measuring, Modeling, and Reproducing Material Appearance 2015: 939807 - [c83]Vaclav Remes, Michal Haindl:
Classification of breast density in X-ray mammography. IWCIM 2015: 1-5 - [c82]Michal Haindl, Vojtech Havlícek:
Color texture restoration. RAM/CIS 2015: CIS:13-18 - [c81]Radek Richtr, Michal Haindl:
Dynamic texture editing. SCCG 2015: 133-140 - [i6]Michal Haindl, Matej Sedlácek, Radomír Vávra:
Virtual Reconstruction of Cultural Heritage Artifacts. ERCIM News 2015(103) (2015) - 2014
- [c80]Michal Haindl, Stanislav Mikes:
Unsupervised Image Segmentation Contest. ICPR 2014: 1484-1489 - [c79]Michal Haindl, Mikulás Krupicka:
Accurate Detection of Non-Iris Occlusions. SITIS 2014: 49-56 - [c78]Michal Haindl, Vaclav Remes:
Adaptive Model-Based Mammogram Enhancement. SITIS 2014: 65-72 - 2013
- [b1]Michal Haindl, Jirí Filip:
Visual Texture: Accurate Material Appearance Measurement, Representation and Modeling. Advances in Computer Vision and Pattern Recognition, Springer 2013, ISBN 978-1-4471-4901-9 - [c77]Michal Haindl, Mikulás Krupicka:
Non-iris occlusions detection. BTAS 2013: 1-6 - [c76]Michal Havlícek, Michal Haindl:
A Moving Average Bidirectional Texture Function Model. CAIP (2) 2013: 338-345 - [c75]Michal Haindl, Stanislav Mikes:
Unsupervised Dynamic Textures Segmentation. CAIP (1) 2013: 433-440 - [c74]Michal Haindl, Vaclav Remes:
Efficient textural model-based mammogram enhancement. CBMS 2013: 522-523 - [c73]Jirí Filip, Radomír Vávra, Michal Haindl, Pavel Zid, Mikulás Krupicka, Vlastimil Havran:
BRDF Slices: Accurate Adaptive Anisotropic Appearance Acquisition. CVPR 2013: 1468-1473 - [c72]Michal Haindl, Radek Richtr:
Dynamic Texture Enlargement. SCCG 2013: 5-12 - [i5]Pavel Vácha, Michal Haindl:
Wood Variety Recognition on Mobile Devices. ERCIM News 2013(93) (2013) - [i4]Michal Haindl, Josef Kittler:
Image Understanding - Introduction to the Special Theme. ERCIM News 2013(95) (2013) - 2012
- [j15]Martin Hatka, Michal Haindl:
Advanced Material Rendering in Blender. Int. J. Virtual Real. 11(2): 15-23 (2012) - [c71]Stanislava Simberová, Michal Haindl, Filip Sroubek:
Fine Structure Recognition in Multichannel Observations. DICTA 2012: 1-7 - [c70]Michal Haindl, Vaclav Remes, Vojtech Havlícek:
Potts compound Markovian texture model. ICPR 2012: 29-32 - [c69]Jirí Filip, Michal Haindl, Jaroslav Stancik:
Predicting environment illumination effects on material appearance. ICPR 2012: 2075-2078 - [p1]Michal Haindl:
Visual Data Recognition and Modeling Based on Local Markovian Models. Mathematical Methods for Signal and Image Analysis and Representation 2012: 241-259 - [i3]Michal Haindl, Jirí Filip, Radomír Vávra:
Digital Material Appearance: The Curse of Tera-Bytes. ERCIM News 2012(90) (2012) - 2011
- [j14]Michal Haindl, Vojtech Havlícek, Jirí Grim:
Probabilistic mixture-based image modelling. Kybernetika 47(3): 482-500 (2011) - [j13]Dmitry Chetverikov, Sándor Fazekas, Michal Haindl:
Dynamic texture as foreground and background. Mach. Vis. Appl. 22(5): 741-750 (2011) - [j12]Pavel Vácha, Michal Haindl, Tomás Suk:
Colour and rotation invariant textural features based on Markov random fields. Pattern Recognit. Lett. 32(6): 771-779 (2011) - [c68]Pavel Vácha, Michal Haindl:
Texture Recognition Using Robust Markovian Features. MUSCLE 2011: 126-137 - [c67]Michal Haindl, Vojtech Havlícek:
A Plausible Texture Enlargement and Editing Compound Markovian Model. MUSCLE 2011: 138-148 - [c66]Michal Haindl, Michal Havlícek:
Bidirectional Texture Function Simultaneous Autoregressive Model. MUSCLE 2011: 149-159 - [c65]Jirí Filip, Pavel Vácha, Michal Haindl:
Analysis of Human Gaze Interactions with Texture and Shape. MUSCLE 2011: 160-171 - [c64]Michal Haindl, Jirí Filip:
Advanced textural representation of materials appearance. SIGGRAPH Asia Courses 2011: 1:1-1:84 - [c63]Martin Hatka, Michal Haindl:
BTF rendering in blender. VRCAI 2011: 265-272 - [i2]Stanislav Mikes, Michal Haindl, Radek Holub:
National Gallery in Prague. ERCIM News 2011(86) (2011) - 2010
- [c62]Pavel Vacha, Michal Haindl:
Natural Material Recognition with Illumination Invariant Textural Features. ICPR 2010: 858-861 - [c61]Jirí Filip, Michal Haindl, Michael J. Chantler:
Gaze-Motivated Compression of Illumination and View Dependent Textures. ICPR 2010: 862-865 - [c60]Michal Haindl, Vojtech Havlícek:
A Compound MRF Texture Model. ICPR 2010: 1792-1795 - [c59]Michal Haindl, Martin Hatka:
Near-Regular BTF Texture Model. ICPR 2010: 2114-2117 - [c58]Michal Haindl, Pavel Zid, Radek Holub:
Range video segmentation. ISSPA 2010: 369-372 - [c57]Michal Haindl, Vojtech Havlícek, Jirí Grim:
Colour texture representation based on multivariate Bernoulli mixtures. ISSPA 2010: 578-581 - [c56]Jirí Filip, Pavel Vácha, Michal Haindl, Patrick R. Green:
A Psychophysical Evaluation of Texture Degradation Descriptors. SSPR/SPR 2010: 423-433 - [c55]Pavel Vácha, Michal Haindl:
Content-Based Tile Retrieval System. SSPR/SPR 2010: 434-443 - [i1]Michal Haindl, Jirí Filip, Martin Hatka:
Realistic Material Appearance Modelling. ERCIM News 2010(81) (2010)
2000 – 2009
- 2009
- [j11]Jirí Filip, Michal Haindl:
Bidirectional Texture Function Modeling: A State of the Art Survey. IEEE Trans. Pattern Anal. Mach. Intell. 31(11): 1921-1940 (2009) - [j10]Jirí Filip, Mike J. Chantler, Michal Haindl:
On uniform resampling and gaze analysis of bidirectional texture functions. ACM Trans. Appl. Percept. 6(3): 18:1-18:15 (2009) - [j9]Jirí Grim, Petr Somol, Michal Haindl, Jan Danes:
Computer-Aided Evaluation of Screening Mammograms Based on Local Texture Models. IEEE Trans. Image Process. 18(4): 765-773 (2009) - [j8]Giuseppe Scarpa, Raffaele Gaetano, Michal Haindl, Josiane Zerubia:
Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation. IEEE Trans. Image Process. 18(8): 1830-1843 (2009) - [c54]Michal Haindl, Martin Hatka:
Near-Regular Texture Synthesis. CAIP 2009: 1138-1145 - [c53]Michal Haindl, Vojtech Havlícek:
Texture Editing Using Frequency Swap Strategy. CAIP 2009: 1146-1153 - [c52]Pavel Vacha, Michal Haindl:
Illumination invariant and rotational insensitive textural representation. ICIP 2009: 1333-1336 - [c51]Michal Haindl, Stanislav Mikes, Pavel Vacha:
Illumination invariant unsupervised segmenter. ICIP 2009: 4025-4028 - [c50]Michal Haindl, Stanislav Mikes, Pavel Pudil:
Unsupervised Hierarchical Weighted Multi-segmenter. MCS 2009: 272-282 - 2008
- [j7]Jirí Filip, Mike J. Chantler, Patrick R. Green, Michal Haindl:
A psychophysically validated metric for bidirectional texture data reduction. ACM Trans. Graph. 27(5): 138 (2008) - [c49]Jirí Filip, Mike J. Chantler, Michal Haindl:
On optimal resampling of view and illumination dependent textures. APGV 2008: 131-134 - [c48]Michal Haindl, Vojtech Havlícek, Jirí Grim:
Probabilistic Discrete Mixtures Colour Texture Models. CIARP 2008: 675-682 - [c47]Jirí Filip, Michal Haindl:
Fast and reliablePCA-based temporal segmentation of video sequences. ICPR 2008: 1-4 - [c46]Michal Haindl, Stanislav Mikes:
Unsupervised mammograms segmentation. ICPR 2008: 1-4 - [c45]Michal Haindl, Stanislav Mikes:
Texture segmentation benchmark. ICPR 2008: 1-4 - [c44]Pavel Vacha, Michal Haindl:
Illumination invariants based on Markov random fields. ICPR 2008: 1-4 - 2007
- [j6]Jirí Filip, Michal Haindl:
BTF modelling using BRDF texels. Int. J. Comput. Math. 84(9): 1267-1283 (2007) - [j5]Michal Haindl, Jirí Filip:
Extreme Compression and Modeling of Bidirectional Texture Function. IEEE Trans. Pattern Anal. Mach. Intell. 29(10): 1859-1865 (2007) - [c43]Michal Haindl, Jirí Grim, Stanislav Mikes:
Texture Defect Detection. CAIP 2007: 987-994 - [c42]Jana Novovicová, Petr Somol, Michal Haindl, Pavel Pudil:
Conditional Mutual Information Based Feature Selection for Classification Task. CIARP 2007: 417-426 - [c41]Pavel Vacha, Michal Haindl:
Demonstration of image retrieval based on illumination invariant textural MRF features. CIVR 2007: 135-137 - [c40]Pavel Vacha, Michal Haindl:
Image retrieval measures based on illumination invariant textural MRF features. CIVR 2007: 448-454 - [c39]Giuseppe Scarpa, Michal Haindl, Josiane Zerubia:
A Hierarchical Finite-State Model for Texture Segmentation. ICASSP (1) 2007: 1209-1212 - [c38]Michal Haindl, Stanislav Mikes, Giuseppe Scarpa:
Unsupervised Detection of Mammogram Regions of Interest. KES (3) 2007: 33-40 - [c37]Michal Haindl, Stanislav Mikes:
Unsupervised Texture Segmentation Using Multiple Segmenters Strategy. MCS 2007: 210-219 - [c36]Giuseppe Scarpa, Michal Haindl, Josiane Zerubia:
A Hierarchical Texture Model for Unsupervised Segmentation of Remotely Sensed Images. SCIA 2007: 303-312 - [c35]Michal Haindl, Stanislava Simberová:
Validation of classical and blind criteria for image quality evaluation. SIP 2007: 213-218 - [e1]Michal Haindl, Josef Kittler, Fabio Roli:
Multiple Classifier Systems, 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings. Lecture Notes in Computer Science 4472, Springer 2007, ISBN 978-3-540-72481-0 [contents] - 2006
- [c34]Jirí Grim, Petr Somol, Michal Haindl, Pavel Pudil:
Color Texture Segmentation by Decomposition of Gaussian Mixture Model. CIARP 2006: 287-296 - [c33]Michal Haindl, Petr Somol, Dimitrios Ververidis, Constantine Kotropoulos:
Feature Selection Based on Mutual Correlation. CIARP 2006: 569-577 - [c32]Michal Haindl, Pavel Zid:
Multimodal Range Image Segmentation by Curve Grouping. ICPR (4) 2006: 9-12 - [c31]Jirí Filip, Michal Haindl, Dmitry Chetverikov:
Fast Synthesis of Dynamic Colour Textures. ICPR (4) 2006: 25-28 - [c30]Giuseppe Scarpa, Michal Haindl:
Unsupervised Texture Segmentation by Spectral-Spatial-Independent Clustering. ICPR (2) 2006: 151-154 - [c29]Michal Haindl, Stanislav Mikes:
Unsupervised Texture Segmentation Using Multispectral Modelling Approach. ICPR (2) 2006: 203-206 - [c28]Jirí Grim, Michal Haindl, Petr Somol, Pavel Pudil:
A Subspace Approach to Texture Modelling by Using Gaussian Mixtures. ICPR (2) 2006: 235-238 - [c27]Michal Haindl, Pavel Vacha:
Illumination Invariant Texture Retrieval. ICPR (3) 2006: 276-279 - [c26]Jirí Filip, Michal Haindl:
BTF Modelling Using BRDF Texels. IWICPAS 2006: 475-484 - 2005
- [c25]Michal Haindl, Stanislav Mikes:
Colour Texture Segmentation Using Modelling Approach. ICAPR (2) 2005: 484-491 - [c24]Michal Haindl, Stanislava Simberová:
Restoration of Multitemporal Short-Exposure Astronomical Images. SCIA 2005: 1037-1046 - [c23]Michal Haindl, Martin Hatka:
A Roller - Fast Sampling-Based Texture Synthesis Algorithm. WSCG (Short Papers) 2005: 93-96 - [c22]Petr Somol, Michal Haindl:
Novel Path Search Algorithm for Image Stitching and Advanced Texture Tiling. WSCG (Full Papers) 2005: 155-162 - 2004
- [c21]Michal Haindl, Jirí Filip:
A Fast Probabilistic Bidirectional Texture Function Model. ICIAR (2) 2004: 298-305 - [c20]Michal Haindl, Stanislav Mikes:
Model-Based Texture Segmentation. ICIAR (2) 2004: 306-313 - [c19]Jirí Filip, Michal Haindl:
Non-linear Reflectance Model for Bidirectional Texture Function Synthesis. ICPR (1) 2004: 80-83 - [c18]Michal Haindl, Jirí Grim, Petr Somol, Pavel Pudil, Mineichi Kudo:
A Gaussian Mixture-Based Colour Texture Model. ICPR (3) 2004: 177-180 - [c17]Michal Haindl, Jirí Filip, Michael Arnold:
BTF Image Space Utmost Compression and Modelling Method. ICPR (3) 2004: 194-197<