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Pedestrian detection is a key problem in many computer vision applications, especially in surveillance and security systems. To this end, information integration from different imaging modalities, such as thermal infrared and visible spectrum, can significantly improve the detection rate in respect to mono-modal strategies. For this reason, an effective fusion scheme is necessary to combine the information...
In this paper, we introduce a torus manifold-based temporal super resolution method for gait recognition from low frame-rate videos with view transitions. Given a low frame-rate gait sequence with view transition from an unknown person, we estimate three unknowns: view, phase, and style. We estimate view by walking trajectory and camera information, phase by dynamic programming using multiview exemplar...
Person-dependent appearance changes tend to increase difficulties in automatic facial expression recognition. Although one can use neutral face images to reduce the personal variations, acquisition of neutral face images may not always be possible in real cases. In order to remove the person-dependent influence from expressive images, we propose a dual subspace nonnegative matrix factorization (DSNMF)...
This paper proposes a method to learn deformation parameters off-line for fast multimodal registration of ultrasound and magnetic resonance prostate images during ultrasound guided needle biopsy. The registration method involves spectral clustering of the deformation parameters obtained from a spline-based nonlinear diffeomorphism between training magnetic resonance and ultrasound prostate images...
Complementary information, when combined in the right way, is capable of improving clustering and segmentation problems. In this paper, we show how it is possible to enhance motion segmentation accuracy with a very simple and inexpensive combination of complementary information, which comes from the column and row spaces of the same measurement matrix. We test our approach on the Hopkins155 dataset...
Human hand is composed of structures called carpal bones, metacarpal bones and phalanges (which form the fingers). Typically, fingerprint matching is used for personal authentication, with images & features obtained from the “tip” of the fingers, ie. distal phalanges (sections, digits). In this study, we report fingerprint minutiae matching results, with images obtained from proximal and middle...
We present a new method for the detection of multiple homographies in image pairs. Our aim is to show that we can approach the optimal solution in a short time using an approach based on the well-known RANSAC algorithm. Given feature correspondences between two similar images, our algorithm iteratively generates homography hypotheses using a suitable sampling, optimizes the promising hypotheses and...
Geometric reconstruction from image collections is a classical computer vision problem. The problem essentially consists of two steps; First, the identification of matches and assembling of point tracks, and second, multiple view geometry computations. In this paper we address the problem of constructing point tracks using graph theoretical algorithms. From standard descriptor matches between all...
We present a sparse representation-based method for detecting adventitious lung sounds in low-quality auscultation signals. Since the noise cannot be represented sparsely by any bases, we can extract clear breath sounds and adventitious sounds from noisy electronic auscultation signals via the sparse representation. Using these clear sound components, we measure the level of abnormality, and robustly...
In this paper, we propose a novel active contour method for image segmentation, which utilizes the advantages of the GAC and the LRAC methods. We consider the smoothing force of the GAC method and local region-based force of the LRAC method. The advantages of our method are as follows. First the proposed method a new region-based signed pressure force function, which can efficiently stop the contours...
Photometric stereo algorithms produce a map of normal directions from the input images. The 3D surface can be reconstructed from this normal map. Existing surface reconstruction works often assume the normal map is integrable but contaminated by small scale non-integrable noise. However, real surfaces often contain large discontinuities such as occlusion boundaries and sharp depth changes, which break...
Active learning traditionally assumes that the oracle is capable of providing labeling information for each query instance. In reality, the oracle might have no information for some queries and cannot provide accurate label but only answers “I don't know the label”. We focus on this problem and provide a unified objective function to ensure that each query instance submitted to the oracle is the one...
Domain adaptation algorithms that handle shifts in the distribution between training and testing data are receiving much attention in computer vision. Recently, a Grassmann manifold-based domain adaptation algorithm that models the domain shift using intermediate subspaces along the geodesic connecting the source and target domains was presented in [6]. We build upon this work and propose replacing...
In this paper, we present a method of robust tracking by accounting for hard negatives (i.e., distractors) of the tracking target explicitly. Our method extends the recently proposed Tracking-Learning-Detection (TLD) approach [7] in two aspects: (i) When learning the on-line fern detector, instead of using a set of features which are first randomly generated and then fixed throughout the tracking,...
It is suggested how a Markov random field can be used for object tracking with context information. The tracking is formulated as a two layer process. In the first phase, the image is represented by a set of feature points which are tracked by a standard tracker. In the second phase, the proposed semi-supervised learning and labeling algorithm is used to label the points to three classes — object,...
This paper proposes a method for estimating the human performance of pedestrian detectability from in-vehicle camera images in order to warn a driver of the positions of pedestrians in an appropriate timing. By introducing features related to visual search and motion of the target, the proposed method estimates the detectability of pedestrians accurately. Support Vector Regression (SVR) is used to...
Sparsity-based super-resolution has attracted lots of attention. Due to the high dimensionality of image data, sparsity-based methods are often in a patch-wise manner and simply impose the smoothness constraints on the overlapped regions between reconstructed patches. However, the imposed smoothness constraint is commonly weak to regularize super-resolution problem when the observed low-resolution...
In this paper, a novel example based method is proposed to solve the remote sensing pan-sharpening problem, utilizing an implicit non-parametric learning framework. The high resolution (HR) and downsam-pled panchromatic (PAN) images are used to train the high/low resolution patch pair dictionaries. Based on the perspective of locally linear embedding (LLE), every patch in each multi-spectral (MS)...
This paper presents a learning-based method called image super-resolution (SR) for generating a high-resolution (HR) image from a single low-resolution (LR) image. Recent research investigated the image SR problem using sparse coding, which is based on good reconstruction of any image local patch by a sparse linear combination of atoms from an overcomplete dictionary. However, sparse-coding-based...
Feature plays an important role in pedestrian detection, and considerable progress has been made on shape-based descriptors. However, color cues have barely been devoted to detection tasks, seemingly due to the variable appearance of pedestrians. In this paper, Color Maximal-Dissimilarity Pattern (CMDP) is proposed to encode color cues by two core operations, i.e., oriented filtering and max-pooling,...
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