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We present a biologically motivated manifold learning framework for image set classification inspired by Independent Component Analysis for Grassmann manifolds. A Grassmann manifold is a collection of linear subspaces, such that each subspace is mapped on a single point on the manifold. We propose constructing Grassmann subspaces using Independent Component Analysis for robustness and improved class...
The research of printed source identification is generally processed by scanned images which are limited by the scanner resolution. The accuracy of source identification is also bound by this limitation. In this study, microscopic images are used for printed source identification based on its high magnification capability for detailed texture and structure information. To explore the relationship...
Conventional Image Retargeting methods aim to preserve the salient regions in an image using As Similar as Possible (ASAP) energy formulation or As Rigid as Possible (ARAP) energy formulation. ASAP energy formulation preserves the shape of the salient object while the scale of salient object can get distorted in the retargeted image. On the contrary, ARAP energy formulation preserves the scale of...
High Efficiency Video Coding is the latest and most advanced video coding standard. It supports various Group Of Pictures (GOP) sizes and types such as low delay and random access. The size of the GOP substantially influences the temporal coding process. Therefore, a suitable GOP selection strategy can have a significant impact in the compression efficiency. In this paper, a strategy for GOP selection...
Fixed camera videos are obtained/used by surveillance, teleconference, remote lecturing. Since it is one of the most fundamental camera movement techniques, it is also frequently used in studio shots, drama/movie scenes. In this paper, simple and efficient coding method for such fixed camera videos is proposed. The proposal significantly improves the coding efficiency and generated bitstream is fully...
We present a novel approach to segment text lines from handwritten document images. In contrast to existing approaches which mainly use hand-designed features or heuristic rules to estimate the location of text lines, we train a fully convolutional network (FCN) to predict text line structure in document images. By using the FCN, a line map which is a rough estimation of text line is obtained. From...
Most electro-photographic printers prefer clustered-dot halftone textures for rendering smooth and stable prints. Clustered-dot halftone patterns can be periodic or aperiodic. As periodic clustered-dot halftone can lead to undesirable moiré patterns, stochastic clustered-dot halftone textures are more preferred. There are available different screening methods to generate stochastic clustered-dot halftone...
Current research in computer vision and machine learning has demonstrated some great abilities at detecting and recognizing objects in natural images. The promising results in these areas have inspired research towards solving more complex multi-modal learning problems in the image/video domains such as automatic annotation, segmentation, labelling, and generic understanding. Although solutions have...
In saliency object detection, inappropriate boundary-background priors is known to degrade performance in challenging image datasets, and even may lead to ‘inverse’ results when saliency regions are attached to the image boundaries. This is an active field where many works have proposed various techniques to lessen such degradation by inappropriate boundary-background priors. Although the use of boundary-background...
Traditional models for saliency analysis in satellite images cannot genuinely mimic the selection mechanism of human vision system. Furthermore, feature selection needs variant considering the complexity of data distribution of different satellite images thereby not being one-size-fits-all. Aiming at these problems, we propose a novel model based on sparse representation for saliency analysis with...
We developed an optical distortion correction technique for an eyeglasses-type wearable device using a multi-mirror array (MMA). This wearable device is small and light weight, but optics using MMA can cause optical distortions, such as geometric distortion and chromatic aberration of magnification, that depend on the user's pupil distance and degrade the visibility of displayed virtual images. We...
In this paper, we propose a novel hierarchical method for remote sensing image classification. The proposed approach integrates an explicit hierarchical graph-based classifier, which uses a quad-tree structure to model multiscale interactions, and a third order Markov mesh random field to deal with pixel wise contextual information in the same scale. The choice of a quad-tree and the third order Markov...
While conventional synthesis dictionary learning approaches have demonstrated tremendous success in various pattern recognition problems, the dictionary pair learning, i.e., jointly learning an analysis dictionary and a synthesis dictionary is still an open problem. Furthermore, the performance of traditional supervised dictionary learning methods is often limited by the amount of labeled training...
The difficult acquisition of labeled data and the misalignment of local matching are major obstacles to apply person re-identification in real scenarios. To alleviate these problems, we propose an unsupervised method, called locality-constrained Earth Mover's Distance (LC-EMD), to learn the optimal measure between image pairs. Specifically, Gaussian mixture models (GMMs) are learned as signatures...
Most state-of-the-art dictionary learning algorithms (DLAs) are iterative, and must begin with an initial estimate of the dictionary, referred to as the seed. A seed can be generated randomly, but it has been shown that choosing a more intelligent seed often yields a better solution. For example, a seed inferred using data from a related problem, or one handcrafted based on a priori knowledge of the...
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Lossless image coding process predicts the value of current pixel from previously decoded pixel values. Then the prediction error is classified according to the context model. This classification splits the sources with different distributions and hence reduce the total entropy of the prediction error signals. In the literature, the predictor has been intensively studied. Some evolutionary approaches...
Conventional autofocus methods based on contrast detection are often unable to reliably decide the direction of initial lens movement. In this paper, we show that even using the disparity data obtained from blurry stereo images can effectively solve the problem. This approach is developed for stereo cameras with adjustable focal distance. Such stereo cameras provide sharp images over a wide range...
In this paper, a tetrahedral mesh-based approach is investigated for 3D image segmentation on a given image volume. We present a series of algorithms to generate high quality, feature-sensitive, and adaptive meshes to partition a 3D volume, where the 3D Canny edge detector is utilized to preserve important feature boundaries in the generated tetrahedral mesh. Each cluster of voxels within a tetrahedron...
High efficiency video coding (HEVC) standard is within the block-based hybrid coding framework, which essentially adopts prediction unit (PU) as the basic motion compensation unit. However, in the case of tiny motion, the actual motion vectors (MVs) for each sample may differ from the PU's MV, thus resulting in more residual energy. In this paper, a novel pixel-wise motion refinement method (PMR)...
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