Prohlížení Publikační činnost - 13133 dle autora "Matas, Jiří"

Zobrazují se záznamy 1-20 z 40

    • A voting strategy for visual ego-motion from stereo 

      Autor: Obdržálek, Štěpán; Matas, Jiří
      (IEEE, 2010-06)
      We present a procedure for egomotion estimation from visual input of a stereo pair of video cameras. The 3D egomotion problem, which has six degrees of freedom in general, is simplified to four dimensions and further ...

    • AdaBoost with Totally Corrective Updates for Fast Face Detection 

      Autor: Šochman, Jan; Matas, Jiří
      (IEEE, 2004-05)
      An extension of the AdaBoost learning algorithm is proposed and brought to bear on the face detection problem. In each weak classifier selection cycle, the novel totally corrective algorithm reduces aggressively the upper ...

    • Adaptive Parameter Optimization for Real-time Tracking 

      Autor: Zimmermann, Karel; Svoboda, Tomáš; Matas, Jiří
      (IEEE, 2007-10)
      Adaptation of a tracking procedure combined in a common way with a Kalman filter is formulated as an constrained optimization problem, where a trade-off between precision and loss-of-lock probability is explicitly taken ...

    • Colour-Based Object Recognition for Video Annotation 

      Autor: Koubaroulis, Dirnitrios; Matas, Jiří; Kittler, Josef
      (IEEE, 2002)
      We propose a colour-based object recognition method for video annotation. The semantic gap between image measurements and symbolic labelling is bridged by assuming the existence of objects whose appearance can be associated ...

    • Construction of Precise Local Affine Frames 

      Autor: Mikulik, Andrej; Matas, Jiří; Perd’och, Michal; Chum, Ondřej
      (IEEE, 2010-08)
      We propose a novel method for the refinement of Maximally Stable Extremal Region (MSER) boundaries to sub-pixel precision by taking into account the intensity function in the 2 × 2 neighborhood of the contour points. The ...

    • Dense Linear-Time Correspondences for Tracking 

      Autor: Obdržálek, Štěpán; Perd’och, Michal; Matas, Jiří
      (IEEE, 2008-06)
      A novel method is proposed for the problem of frame-to-frame correspondence search in video sequences. The method, based on hashing of low-dimensional image descriptors, establishes dense correspondences and allows large ...

    • Efficient Representation of Local Geometry for Large Scale Object Retrieval 

      Autor: Perd’och, Michal; Chum, Ondřej; Matas, Jiří
      (IEEE, 2009-06)
      State of the art methods for image and object retrieval exploit both appearance (via visual words) and local geometry (spatial extent, relative pose). In large scale problems, memory becomes a limiting factor - local ...

    • Efficient Sequential Correspondence Selection by Cosegmentation 

      Autor: Čech, Jan; Matas, Jiří; Perd’och, Michal
      (IEEE, 2008-06)
      In many retrieval, object recognition and wide baseline stereo methods, correspondences of interest points are established possibly sublinearly by matching a compact descriptor such as SIFT. We show that a subsequent ...

    • Efficient Sequential Correspondence Selection by Cosegmentation 

      Autor: Čech, Jan; Matas, Jiří; Perd’och, Michal
      (IEEE, 2010-09)
      In many retrieval, object recognition, and wide-baseline stereo methods, correspondences of interest points (distinguished regions) are commonly established by matching compact descriptors such as SIFTs. We show that a ...

    • Epipolar Geometry Estimation via RANSAC Benefits from the Oriented Epipolar Constraint 

      Autor: Chum, Ondřej; Werner, Tomáš; Matas, Jiří
      (IEEE, 2004-08)
      The efficiency of epipolar geometry estimation by RANSAC is improved by exploiting the oriented epipolar constraint. Performance evaluation shows that the enhancement brings up to a two-fold speed-up. The orientation test ...

    • Epipolar Geometry from Two Correspondences 

      Autor: Perd’och, Michal; Matas, Jiří; Chum, Ondřej
      (IEEE, 2006)
      A novel algorithm for robust RANSAC-like estimation of epipolar geometry (of uncalibrated camera pair) from two correspondences of local affine frames (LAFs) is presented. Each LAF is constructed from three points independently ...

    • Face-TLD: Tracking-Learning-Detection applied to faces 

      Autor: Kalal, Zdenek; Mikolajczyk, Krystian; Matas, Jiří
      (IEEE, 2010-09)
      A novel system for long-term tracking of a human face in unconstrained videos is built on Tracking-Learning-Detection (TLD) approach. The system extends TLD with the concept of a generic detector and a validator which is ...

    • Fast Detection of Multiple Textureless 3-D Objects 

      Autor: Cai, Hongping; Werner, Tomáš; Matas, Jiří
      (Springer, 2013)
      We propose a fast edge-based approach for detection and approximate pose estimation of multiple textureless objects in a single image. The objects are trained from a set of edge maps, each showing one object in one pose. ...

    • Forward-Backward Error: Automatic Detection of Tracking Failures 

      Autor: Kalal, Zdenek; Mikolajczyk, Krystian; Matas, Jiří
      (IEEE, 2010-08)
      This paper proposes a novel method for tracking failure detection. The detection is based on the Forward-Backward error, i.e. the tracking is performed forward and backward in time and the discrepancies between these two ...

    • Geometric Hashing with Local Af ne Frames 

      Autor: Chum, Ondřej; Matas, Jiří
      (IEEE, 2006-06)
      We propose a novel representation of local image structure and a matching scheme that are insensitive to a wide range of appearance changes. The representation is a collection of local affine frames that are constructed ...

    • Geometric min-Hashing: Finding a (Thick) Needle in a Haystack 

      Autor: Chum, Ondřej; Perd’och, Michal; Matas, Jiří
      (IEEE, 2009-06)
      We propose a novel hashing scheme for image retrieval, clustering and automatic object discovery. Unlike commonly used bag-of-words approaches, the spatial extent of image features is exploited in our method. The geometric ...

    • Guest Editors’ Introduction to the Special Section on CVPR Papers 

      Autor: Baker, Simon; Matas, Jiří; Zabih, Ramin
      (IEEE, 2008-10)

    • Image Matching and Retrieval by Repetitive Patterns 

      Autor: Doubek, Petr; Matas, Jiří; Perd’och, Michal; Chum, Ondřej
      (IEEE, 2010-08)
      Detection of repetitive patterns in images has been studied for a long time in computer vision. This paper discusses a method for representing a lattice or line pattern by shift-invariant descriptor of the repeating element. ...

    • Improving Descriptors for Fast Tree Matching by Optimal Linear Projection 

      Autor: Mikolajczyk, Krystian; Matas, Jiří
      (IEEE, 2007-10)
      In this paper we propose to transform an image descriptor so that nearest neighbor (NN) search for correspondences becomes the optimal matching strategy under the assumption that inter-image deviations of corresponding ...

    • Inter-stage Feature Propagation in Cascade Building with AdaBoost 

      Autor: Šochman, Jan; Matas, Jiří
      (IEEE, 2004-08)
      A modification of the cascaded detector with the Ada-Boost trained stage classifiers is proposed and brought to bear on the face detection problem. The cascaded detector is a sequential classifier with the ability of early ...