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Speech to Speech translation (S2ST) systems are very important for processing by which a spoken utterance in one language is used to produce a spoken output in another language. In S2ST techniques, so far, linguistic information has been mainly adopted without para- and non-linguistic information (emotion, individuality and gender, etc.). Therefore, this systems have a limitation in synthesizing affective...
This paper motivates the use of RASTA-MFCC (RelAtive SpecTrA-Mel Frequency Cepstral Coefficients) feature and GMM-UBM modeling for text independent voice based students' attendance system under noisy environment. MFCC has been identified as an efficient feature for identifying the speaker because it extracts speaker specific information. The performance of even best speaker identification system with...
We propose a reliable 3D position and pose recognition method for complicated scenes including randomly stacked objects. Conventional methods use a small number of features selected by analyzing a target object model for recognition. The small number contributes to high-speed recognition, but actually the features include both "true" and "false" features. True features exist only...
Can privacy of individuals in an anonymized social graph be threatened by a handful of structural features i.e., Without knowledge of link-level connectivity? The answer is yes. We define threatening privacy as being able to narrow down each anonymized individual's identity to a small set of known individuals that is most likely to include the anonymized individual. We call this set the Identity+...
Visual attention is one of the most important mechanisms in the human visual perception. Recently, its modeling becomes a principal requirement for the optimization of the image processing systems. Numerous algorithms have already been designed for 2D saliency prediction. However, only few works can be found for 3D content. In this study, we propose a saliency model for stereoscopic 3D video. This...
Automated Fingerprint Identification Systems (AFIS) currently rely only on Level 1 and Level 2 features. But these features are not much helpful for forensic experts as the experiment deals with partial to full print matching of latent fingerprint. Forensic experts takes the advantage of extended feature proposed by "Committee to Define an Extended Fingerprint Feature Set" (CDEFFS). This...
Most existing rat able aspect generating methods for aspect mining focus on identifying and rating aspects of reviews with overall ratings, while huge amount of unrated reviews are beyond their ability. This drawback motivates the research problem in this paper: predicting aspect ratings and overall ratings for unrated reviews. To solve this problem, we novelly propose a topic model based on Latent...
3D garment has complex and flexible shape. In order to obtain realistic texture mapping results with various garment models, an efficient and simple mesh parameterization method is presented in this paper. The key idea in this work is to partition the garment model using geometrical feature line that is composed of several mesh edges and to parameterize the mesh facet after partitioning. We achieve...
Most edge detection methods are based on first-order or second-order differential. These are local methods. Using Hausdorff distance to quantify the strength of the edge is a method with a holistic property. Firstly, down sample the image, and split the image into two sets. Secondly, get the feature image by assigning a value for each point using the scalar field map constructed by Hausdorff distance...
Abstract-Computer vision techniques such as Structurefrom- Motion (SfM) and object recognition tend to fail on scenes with highly reflective objects because the reflections behave differently to the true geometry of the scene. Such image sequences may be treated as two layers superimposed over each other - the nonreflection scene source layer and the reflection layer. However, decomposing the two...
In modern times, it has become very essential for e-commerce businesses to empower their end customers to write reviews about the services that they have utilized. Such reviews provide vital sources of information on these products or services. This information is utilized by the future potential customers before deciding on purchase of new products or services. These opinions or reviews are also...
Palm print is an emerging type of biometric that attracts researchers in biometrics area. As compared to the other biometric traits such as face, fingerprint and iris, the image quality of a fingerprint is robust with more information can be employed even though it is in low resolution. A new approach in feature extraction called evolution of kernel principal component analysis (Evo-KPCA) was proposed...
In this paper, we propose a robust curved lane marking detection method by first detecting a straight lane and applying a geometric model of that detected straight lane. In our proposed method, we first detect the straight line and generate 13 candidates of the curved lane by applying a geometric model. We then vote those candidates on the feature image and consider the candidate which acquires the...
Playing a vital role, saliency has been widely applied for various image analysis tasks, such as content-aware image retargeting, image retrieval and object detection. It is generally accepted that saliency detection can benefit from the integration of multiple visual features. However, most of the existing literatures fuse multiple features at saliency map level without considering cross-feature...
In this study, digital image processing was incorporated to eliminate the Subjectiveness of manual inspection of diseases in rice plant and accurately identify the three common diseases to Philippine's farmlands: (1) Bacterial leaf blight, (2) Brown spot, and (3) Rice blast. The image processing section was built using MATLAB functions and it comprises techniques such as image enhancement, image segmentation,...
Nowadays the rapid development in the area of human-computer interaction has given birth to a growing interest on detecting different affective states through smart devices. By using the modern sensor equipment, we can easily collect electroencephalogram (EEG) signals, which capture the information from central nervous system and are closely related with our brain activities. Through the training...
Traditional multi-class image classification needs a large number of training samples for building a classifier model. However, it is very time-consuming and costly to obtain labels for a large number of training samples from human experts. Active learning is a feasible solution. This paper proposes a maximum classification optimization method (MCO) for actively selecting unlabeled images to acquire...
Human activity detection from videos is very challenging, and has got numerous applications in sports evalution, video surveillance, elder/child care, etc. In this research, a model using sparse representation is presented for the human activity detection from the video data. This is done using a linear combination of atoms from a dictionary and a sparse coefficient matrix. The dictionary is created...
We propose a fast and reliable 3D object detection method that can be applied for complicated scenes consisting of randomly stacked objects. The proposed method uses "3D vector pair" that has a common start point and different end points and it has surface normal distribution as the feature descriptor. By considering the observability of vector pairs, the proposed method has been achieved...
In this paper, a novel method is proposed for the Traffic Sign Recognition (TSR) using the Principle Component Analysis (PCA) and the Multi-Layer Perceptrons (MLPs) network. In particular, the candidate signs are individually detected from two chroma components in the YCbCr space and then classified into three shape classes: circle, square, and triangle based on computing the rotated version correlations...
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