Jiri Matas mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Video tracking. His Artificial intelligence study frequently draws connections between adjacent fields such as Machine learning. He has included themes like Contextual image classification, Cognitive neuroscience of visual object recognition, Text detection and Optical character recognition in his Pattern recognition study.
Jiri Matas focuses mostly in the field of Algorithm, narrowing it down to topics relating to Maximally stable extremal regions and, in certain cases, Harris affine region detector, Principal curvature-based region detector, Hessian affine region detector, Epipolar geometry and Geometry. Jiri Matas has researched Video tracking in several fields, including Visualization and Hough transform. His research investigates the connection between Tracking and topics such as Object that intersect with problems in Data mining.
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Object. His study focuses on the intersection of Artificial intelligence and fields such as Machine learning with connections in the field of Benchmark. His research brings together the fields of Robustness and Computer vision.
When carried out as part of a general Pattern recognition research project, his work on Classifier, Feature extraction and Support vector machine is frequently linked to work in Context, therefore connecting diverse disciplines of study. His Algorithm study combines topics in areas such as RANSAC and Homography. In Object, Jiri Matas works on issues like Pose, which are connected to RGB color model.
Jiri Matas spends much of his time researching Artificial intelligence, Computer vision, Algorithm, Pattern recognition and RGB color model. His work in Pose, Pixel, Video tracking, Object and Benchmark are all subfields of Artificial intelligence research. His study ties his expertise on Discriminative model together with the subject of Computer vision.
His Algorithm research includes elements of Sampling, Range, RANSAC and Homography. His Pattern recognition research incorporates themes from Color constancy and Text recognition. His RGB color model research is multidisciplinary, relying on both Margin and Tracking.
Jiri Matas mainly investigates Artificial intelligence, Computer vision, RGB color model, Pattern recognition and Video tracking. His Artificial intelligence research includes themes of Algorithm and Range. His studies in Computer vision integrate themes in fields like Selection and Cluster analysis.
His RGB color model study incorporates themes from Object, Pose and Margin. His biological study spans a wide range of topics, including Pixel and Test set. His Video tracking research incorporates elements of Intersection, Visualization, Discriminative model and Motion blur.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
On combining classifiers
J. Kittler;M. Hatef;R.P.W. Duin;J. Matas.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1998)
Robust wide-baseline stereo from maximally stable extremal regions
Jiri Matas;Ondrej Chum;Martin Urban;Tomás Pajdla.
Image and Vision Computing (2004)
A Comparison of Affine Region Detectors
K. Mikolajczyk;T. Tuytelaars;C. Schmid;A. Zisserman.
International Journal of Computer Vision (2005)
Z. Kalal;K. Mikolajczyk;J. Matas.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
XM2VTSDB: The Extended M2VTS Database
K. Messer;J. Matas;J. Kittler;Juergen Luettin.
Proc. Second International Conference on Audio- and Video-based Biometric Person Authentication (AVBPA'99) (1999)
P-N learning: Bootstrapping binary classifiers by structural constraints
Zdenek Kalal;Jiri Matas;Krystian Mikolajczyk.
computer vision and pattern recognition (2010)
The Visual Object Tracking VOT2015 Challenge Results
Matej Kristan;Jiri Matas;Ale Leonardis;Michael Felsberg.
international conference on computer vision (2015)
The Visual Object Tracking VOT2017 Challenge Results
Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg.
international conference on computer vision (2017)
Matching with PROSAC - progressive sample consensus
O. Chum;J. Matas.
computer vision and pattern recognition (2005)
The Visual Object Tracking VOT2013 Challenge Results
Matej Kristan;Roman Pflugfelder;Ale Leonardis;Jiri Matas.
international conference on computer vision (2013)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: