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An organization that has a lot of personal data can create a deep neural network (DNN), which predicts sensitive attribute values such as the salary and diseases of people based on other attribute values such as age and hobbies. Moreover, by putting this data on the Cloud and providing the functionality of the DNN to other organizations, they can obtain new knowledge and can subsequently create new...
Existing quality assessment methods of contrast-distorted images have excellent performance by obtaining information of reference images. However, in actual life, there are not any reference images. To deal with this problem, we propose a simple yet promising no-reference quality assessment algorithm based on the human perception features for contrast-distorted images. First, human visual perception...
Research in human visual perception has found that the sense of natural scences cannot be conveyed only through lines and edges. It also needs the knowledge of texture regions within the image, which can be obtained through the analysis of higher derivatives. Inspired by the research from neuroscience that high order derivatives can capture the details of image structure, we propose a novel simple...
We present a new content-based visual information retrieval system that applies different existing techniques in a novel way. We use multi-scale local binary patterns to extract a set of features histogram of an image. Then we integrate it with a superpixel-based saliency model to assign weights to the features. Finally we train a group of constrained similarity boundaries using SVM to exploit the...
Research on non-intrusive speech quality assessment (SQA) aims to develop a computational model simulating the human perception of speech signals accurately and automatically without any prior information about the reference clean speech signals. In this paper, we propose to learn a non-intrusive SQA metric based on bag-of-words (BoW) representation of speech signals. In particular, the proposed method...
Perceptual quality evaluation of the retargeting image plays an important role in benchmarking different retargeting methods, as well as guiding or optimizing the retargeting process. The distortions introduced during the retargeting process are mainly categorized into shape distortion and content information loss [1]. The shape distortion measurement is critical to the evaluation of retargeting image...
Reduced-reference (RR) image quality assessment (IQA) aims to use less reference data and achieve higher quality prediction accuracy. Recent researches confirm that the human visual system (HVS) is adapted to extract structural information and is sensitive to structure degradation. Therefore, in this paper, we try to represent image contents with several structural patterns, and measure image quality...
Face recognition is an emergent research area, spanning over multiple disciplines such as image processing, computer vision and signal processing. Moreover, face recognition is also used for identity authentication, security access control and intelligent human-computer interaction. This work compares face recognition methods using local features and global features. The local features were derived...
It is widely known that, for most natural images, appropriate contrast enhancement can usually lead to improved subjective quality. Despite of its importance to image processing, contrast change has largely been overlooked in the current research of image quality assessment (IQA). To fill this void, in this paper we first report a new and dedicated contrast-changed image database (CID2013). The CID2013...
In this paper we use the Earth Movers Distance (EMD) algorithm to measure similarity between shapes for recognizing and searching Arabic words. We have used the Shape Context and the Angular Radial Partitioning descriptors to evaluate matching and recognizing with EMD. Based on the encouraging results of high accuracy and recall, we follow the low-distortion embedding of the Earth Mover's Distance...
Automatic estimation of 3D shape similarity from video is a very important factor for human action analysis, but also a challenging task due to variations in body topology and the high dimensionality of the pose configuration space. We consider the problem of 3D shape similarity in 3D video sequence for different actors and motions. Most current approaches use conventional global features as a shape...
The usage of specifically designed cameras for robust image classification, biometric and surveillance has emerged recently and it inevitably involves multi-modality classification problems. Cross-modality as well as within- and between-class variations jointly produce a significantly complex problem. In this paper, we propose a hierarchical hyperlingual-words based approach towards the aforementioned...
The development of a fully automatic facial expression recognition system is an open problem. Its implications are very important, with applications ranging from machine intelligence and interaction to psychology research. In order to obtain a viable system, it is necessary to get valid parameters to characterize the facial expression in an image or a video sequence. Several different techniques have...
A crucial step in many vision based applications, such as localization and structure from motion, is the data association between a large map of known 3D points and 2D features perceived by a new camera. In this paper, we propose a novel approach to predict the visibility of known 3D points with respect to a query camera in large-scale environments. In our approach, we model the visibility of each...
Image quality assessment (IQA) is very important for many image and video processing applications, e.g. compression, archiving, restoration and enhancement. An ideal image quality metric should achieve consistency between image distortion prediction and psychological perception of human visual system (HVS). Inspired by that HVS is quite sensitive to image local orientation features, in this paper,...
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