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Eye detector and eye tracker have been individually used to solve the task of eye localization in video. Although the eye detection based approach seems to be robust especially in frontal view faces and opened eyes, its performance drops dramatically in the presence of large head pose change and closed eyes. Meanwhile, eye tracking based approaches can estimate closed eyes and eyes in extreme head...
This paper explores the challenge of optimally categorizing regions for man-made environment. We propose using the histogram of oriented gradients (HOG) features for characterizing image regions, and propose an algorithm based on the entropy of HOG to select relevant regions. We also propose a regionsensitive feature selection algorithm for image registration. The algorithms are applied to several...
An automatic text recognizer needs, in first place, to localize the text in the image the more accurately possible. For this purpose, we present in this paper a robust method for text detection. It is composed of three main stages: a segmentation stage to find character candidates, a connected component analysis based on fast-to-compute but robust features to accept characters and discard non-text...
Reading text from scene images is a challenging problem that is receiving much attention, especially since the appearance of imaging devices in low-cost consumer products like mobile phones. This paper presents an easy and fast method to recognize individual characters in images of natural scenes that is applied after an algorithm that robustly locates text on such images. The recognition is based...
We have been manufacturing our own License Plate Recognition (LPR) systems since 1999 for parking lots in Japan. We have implemented a number of enhancements for our latest LPR system and one of the most important enhancements is for ranges of acceptable license-plate attitude angles. We collected 163, 574 actual images so far and we selected 6,648 images randomly from this image database to verify...
Center-surround measurements are widely used for saliency detection but with some disadvantages: 1) Center-surround operation may cause inaccurate segmentation and even involve incorrect detection results; 2) In most situations, only using center-surround feature is not efficient to encode object saliency. To overcome these disadvantages, we describe a novel measurement, namely Corner-Surround Contrast...
This paper presents a method for feature-based 3D object recognition in cluttered scenes. It deals with the problem of non-uniform sampling density which is inherent in typical range sensing methods. We suggest a method operating on polygonal meshes which overcomes the problem by exploiting surface area in both establishing local frames and creating feature descriptors. The method is able to recognize...
A new descriptor called Multi-modal Binary Patterns (MMBP) is proposed for face recognition. It balances well important requirements for real-world applications, including the robustness, discriminative power, and the low computational cost. The proposed algorithm has several desirable properties: 1) it captures information from face image in any direction as it is oriented feature, 2) being a spatial...
Deformable registration of multi-modality medical image remains a challenging research topic. The incorporation of prior information on the expected joint distribution has shown to noticeably improve registration accuracy and robustness. However, direct application of the learned joint histogram makes the algorithm sensitive to the difference between the training data and the test image. This paper...
Local Binary Patterns (LBPs) and Covariance Matrices (CovMs) are two popular kinds of texture descriptors. However, local correlation brought by LBPs and global correlation brought by CovMs could not be directly combined to achieve enhanced discriminative power. This paper develops a powerful descriptor, named COV-LBP. Firstly, we propose a variant of LBPs on Euclidean space, named the LBP Difference...
Indirect immunofluorescence (IIF) imaging is a method used for detection of antinuclear auto-antibodies (ANA) for the diagnosis of autoimmune diseases. We present a feature extraction and classification scheme to classify the fluorescence staining patterns of HEp-2 cells in IIF images. We propose a set of complementary features that are sensitive to staining pattern variations among classes. Our feature...
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