The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We address the person reidentification problem by efficient data representation method. Based on the Relaxed Nonnegative matrix factorization (rNMF) which has no sign constraints on the data matrix and the basis matrix, we consider two regularizations to improve the Relaxed NMF, which are the local manifold assumption and a rank constraint. The local manifold assumption helps preserve the geometry...
This work addresses the task of underwater object recognition in sonar imagery when both human operators and automated algorithms are available. We discuss the issues that have impeded previous attempts at automation, raise key insights related to human perception, present strategies to exploit the skills of humans and computers synergistically, and demonstrate the utility of the proposed approaches...
This paper studies the performance of recorded eye movements and computational visual attention models (i.e. saliency models) in the recognition of emotional valence of an image. In the first part of this study, it employs eye movement data (fixation & saccade) to build image content descriptors and use them with support vector machines to classify the emotional valence. In the second part,...
Recently, many deep networks are proposed to learn hierarchical image representation to replace traditional hand-designed features. To enhance the ability of the generative model to tackle discriminative computer vision tasks (e.g. image classification), we propose a hierarchical deconvolutional network with two biologically inspired properties incorporated, i.e., non-negative sparsity and selectivity...
Robust and efficient detection of cars in urban scenes has many useful applications. This paper introduces a framework for car detection from high-resolution satellite images, wherein a novel extended image descriptor is used to depict the geometric, spectral and colour distribution properties of cars. The proposed framework is based on a sliding-window detection approach and it begins with a pre-prepossessing...
Linear discriminant analysis that takes spatial smoothness into account has been developed and widely used in image processing society. However, two questions remain unanswered. First, which is the best way to incorporate the smoothness property of images with linear discriminant analysis? Second, which is the best representation for the smoothness property of images? To answer the first question,...
In this paper we present a novel people detector that employs discrete optimization for feature selection. Specifically, we use binary integer programming to mine heterogeneous features taking both detection performance and computation time explicitly into consideration. The final trained detector exhibits low Miss Rates with significant boost in frame rate. For example, it achieves a 2.6% less Miss...
Region Connectivity Calculus (RCC) can be used to define the formal grammar describing the relationship between image regions. While RCC provides a possible framework for representation of object part constellations leading to object recognition, little has been done in the direction of RCC for 3D images. Almost all prior RCC representations, such as RCC5/ RCC8/ RCC23/RCC62 are oriented towards 2D...
Image-based kinship recognition is an important problem in the reconstruction and analysis of social networks. Prior studies on image-based kinship recognition have focused solely on pair wise kinship verification, i.e. on the question of whether or not two people are kin. Such approaches fail to exploit the fact that many real-world photographs contain several family members, for instance, the probability...
A new geometric framework, called generalized coupled line camera (GCLC), is proposed to derive an analytic solution to reconstruct an unknown scene quadrilateral and the relevant projective structure from a single or multiple image quadrilaterals. We extend the previous approach developed for rectangle to handle arbitrary scene quadrilaterals. First, we generalize a single line camera by removing...
3D Morph able Model (3DMM) has been widely used in face analysis for many years. The most challenging part of 3DMM is to find the correspondences between 3D points and 2D pixels. Existing methods only use key points, edges, specular highlights and image pixels to complete the task, which are not accurate or robust. This paper proposes a new algorithm called Sparse SIFT Flow (SSF) to improve the reconstruction...
One of the fast similarity search techniques is a binary hashing method that transforms a real-valued vector into a binary code. The similarity between two binary codes is measured by their Hamming distance. In this method, a hash table is often used for realizing the constant time similarity search. The number of accesses to the hash table, however, increases when the number of bits becomes long...
This paper introduces a new descriptor for characterizing and classifying the pixels of texture images by means of General Adaptive Neighborhoods (GANs). The GAN of a pixel is a spatial region surrounding it and fitting its local image structure. The features describing each pixel are then regionbased and intensity-based measurements of its corresponding GAN. In addition, these features are combined...
High incidence cases associated with back pain include intervertebral disc degeneration (IDD), or disc herniation, in the spinal lumbar region, as well as sciatica, pain in the legs due to IDD. This research aims to provide a more accurate and robust segmentation scheme for identification of spine pathologies, to assist with spine surgery planning and simulation. We are developing a minimally supervised...
This paper proposes a 2D code and its decoding method robust against non-uniform, complicated distortions, assuming an application to automatic recognition of a plastic garbage bag. Printing a 2D code on a garbage bag is a promising approach for automatic bag recognition from the perspective of information content and cost. However, a 2D code printed on the bag causes non-uniform distortions because...
The aim of this work is to localize a query mobile photograph by utilizing surveillance images, which naturally provide location information. We cast this cross-device visual localization problem as a classification task. By exploiting the surveillance network to collect reference images, the data acquisition process is significantly facilitated. However, the discrepancy between mobile images and...
In this paper, we present an exemplar-based image in painting technique using the higher order singular value decomposition (HOSVD). The two main steps of the proposed method are determination of patch priority and patch completion. Here we adopt gradient-based priority term. For patch completion, we build a stack of the candidate patches corresponding to the target patch. Then we find the coefficients...
To get high recognition accuracy, we should train the recognizer with sufficient training data to capture characteristics of various handwriting styles and all possible occurring words. However, in most of the cases, available training data are not satisfactory and enough, especially for unseen data. In this paper, we try to improve the recognition accuracy for unseen data with randomly selected training...
Since the document structure carries valuable discriminative information, plenty of efforts have been made for extracting and understanding document structure among which layout analysis approaches are the most commonly used. In this paper, Distance Transform based MSER (DTMSER) is employed to efficiently extract the document structure as a dendrogram of key-regions which roughly correspond to structural...
Text information contained in scene images is very useful for image understanding. In this paper, we propose a high-level representation named stroke bank for scene character recognition. Inspired by the work of object bank, we train stroke detectors and use detectors' maximal output as features. Specifically, we collect training samples for stroke detectors based on labeled key points. We also propose...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.