Papers by Mikuláš Krupička
Computer Graphics Forum, 2016
One of the most accurate yet still practical representation of material appearance is the Bidirec... more One of the most accurate yet still practical representation of material appearance is the Bidirectional Texture Function (BTF). The BTF can be viewed as an extension of Bidirectional Reflectance Distribution Function (BRDF) for additional spatial information that includes local visual effects such as shadowing, interreflection, subsurface-scattering, etc. However, the shift from BRDF to BTF represents not only a huge leap in respect to the realism of material reproduction, but also related high memory and computational costs stemming from the storage and processing of massive BTF data. In this work, we argue that each opaque material, regardless of its surface structure, can be safely substituted by a BRDF without the introduction of a significant perceptual error when viewed from an appropriate distance. Therefore, we ran a set of psychophysical studies over 25 materials to determine so-called critical viewing distances, i.e. the minimal distances at which the material spatial structure (texture) cannot be visually discerned. Our analysis determined such typical distances typical for several material categories often used in interior design applications. Furthermore, we propose a combination of computational features that can predict such distances without the need for a psychophysical study. We show that our work can significantly reduce rendering costs in applications that process complex virtual scenes.
2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems, 2014
Accurate detection of iris eyelids and reflections is the prerequisite for the accurate iris reco... more Accurate detection of iris eyelids and reflections is the prerequisite for the accurate iris recognition, both in near-infrared or visible spectrum measurements. Undected iris occlusions otherwise dramatically decrease the iris recognition rate. This paper presents a fast multispectral iris occlusions detection method based on the underlying multispectral spatial probabilistic iris textural model and adaptive thresholding. The model adaptively learns its parameters on the iris texture part and subsequently checks for iris reflections, eyelashes, and eyelids using the recursive prediction analysis. Our method obtains better accuracy with respect to the previously performed Noisy Iris Challenge Evaluation contest. It ranked first from the 97+2 alternative methods on this large colour iris database.
A photo-realistic representation of material appearance can be achieved by means of bidirectional... more A photo-realistic representation of material appearance can be achieved by means of bidirectional texture function (BTF) capturing a material’s appearance for varying illumination, viewing directions, and spatial pixel coordinates. BTF captures many non-local effects in material structure such as inter-reflections, occlusions, shadowing, or scattering. The acquisition of BTF data is usually time and resource-intensive due to the high dimensionality of BTF data. This results in expensive, complex measurement setups and/or excessively long measurement times. We propose an approximate BTF acquisition setup based on a simple, affordable mechanical gantry containing a consumer camera and two LED lights. It captures a very limited subset of material surface images by shooting several video sequences. A psychophysical study comparing captured and reconstructed data with the reference BTFs of seven tested materials revealed that results of our method show a promising visual quality. As it a...
CBIR Service for Object Identification
Lecture Notes in Computer Science, 2015
This paper proposes an architecture for an exact object detection system. The implementation as w... more This paper proposes an architecture for an exact object detection system. The implementation as well as the communication between individual system components is detailed in the paper. Well known methods for feature detection and extraction were used. Fast and precise method for feature comparison is presented. The proposed system was evaluated by training the dataset and querying the dataset. With 12 Workers, the response time of querying the dataset consisting of $$100\\,000$$ images were just below 20 seconds. Also system trained dataset of this size with same amount of workers in about an hour.
Pattern Recognition Letters, 2015
This paper presents a fast precise unsupervised iris defects detection method based on the underl... more This paper presents a fast precise unsupervised iris defects detection method based on the underlying multispectral spatial probabilistic iris textural model and adaptive thresholding applied to demanding high resolution mobile device measurements. The accurate detection of iris eyelids and reflections is the prerequisite for the accurate iris recognition, both in near-infrared or visible spectrum measurements. The model adaptively learns its parameters on the iris texture part and subsequently checks for iris reflections using the recursive prediction analysis. The method is developed for color eye images from unconstrained mobile devices but it was also successfully tested on the UBIRIS v2 eye database. Our method ranked first from the 97+1 recent Noisy Iris Challenge Evaluation contest alternative methods on this large color iris database using the exact contest data and methodology.
Sensors (Basel, Switzerland), 2014
A photo-realistic representation of material appearance can be achieved by means of bidirectional... more A photo-realistic representation of material appearance can be achieved by means of bidirectional texture function (BTF) capturing a material's appearance for varying illumination, viewing directions, and spatial pixel coordinates. BTF captures many non-local effects in material structure such as inter-reflections, occlusions, shadowing, or scattering. The acquisition of BTF data is usually time and resource-intensive due to the high dimensionality of BTF data. This results in expensive, complex measurement setups and/or excessively long measurement times. We propose an approximate BTF acquisition setup based on a simple, affordable mechanical gantry containing a consumer camera and two LED lights. It captures a very limited subset of material surface images by shooting several video sequences. A psychophysical study comparing captured and reconstructed data with the reference BTFs of seven tested materials revealed that results of our method show a promising visual quality. Spe...
2013 IEEE Conference on Computer Vision and Pattern Recognition
In this paper we introduce unique publicly available dense anisotropic BRDF data measurements. We... more In this paper we introduce unique publicly available dense anisotropic BRDF data measurements. We use this dense data as a reference for performance evaluation of the proposed BRDF sparse angular sampling and interpolation approach. The method is based on sampling of BRDF subspaces at fixed elevations by means of several adaptively-represented, uniformly distributed, perpendicular slices. Although this proposed method requires only a sparse sampling of material, the interpolation provides a very accurate reconstruction, visually and computationally comparable to densely measured reference. Due to the simple slices measurement and method's robustness it allows for a highly accurate acquisition of BRDFs. This in comparison with standard uniform angular sampling, is considerably faster yet uses far less samples.
2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)
The prerequisite for the accurate iris recognition is to detect all iris occlusions which would o... more The prerequisite for the accurate iris recognition is to detect all iris occlusions which would otherwise confuse a recognition method and impair its recognition rate. This paper presents a fast multispectral eyelid, eyelash, and reflection detection method based on the underlying threedimensional spatial probabilistic textural model. The model first adaptively learns its parameters on the flawless iris texture part and subsequently checks for non iris occlusions using the recursive prediction analysis. We provide colour iris occlusion detection results that indicate the advantages of the proposed method and compare it with 97 recent Noisy Iris Challenge Evaluation algorithms.
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Papers by Mikuláš Krupička