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Dental image processing is most immerging field for human identification. Dental features remain more or less invariant over time compared to other identification clues like fingerprint, iris, etc. which are not available in some case of major accidents. The purpose of dental image processing is to match the post-mortem (PM) radiograph with the ante mortem (AM) radiograph based on some characteristic...
Cognitive information processing at higher conceptual levels requires a computational approach to knowledge representation and analysis. Semantic network analysis bridges the gap between probabilistic pattern recognition techniques and symbolic representations by replacing cumbersome and computationally complex forms of logic-based semantic inference common in symbolic approaches with mathematical...
We investigate body soft biometrics capabilities to perform pruning of a hard biometrics database improving both retrieval speed and accuracy. Our pre-classification step based on anthropometric measures is elaborated on a large scale medical dataset to guarantee statistical meaning of the results, and tested in conjunction with a face recognition algorithm. Our assumptions are verified by testing...
Human gait is a complex phenomenon involving the motion of various parts of the body simultaneously in 3 dimensional space. The dynamics of different parts of the body translate the center of gravity from one point to another in the most energy efficient way. These body dynamics as well as the static parameters of different body parts contribute to gait recognition. Studies have been performed to...
Human identification at a distance has recently gained growing interest from computer vision researchers. This paper presents an automatic gait recognition system that recognizes a person by the way they walk. The gait signature is obtained based on the angle and the contour of the silhouette. For each image sequence, background subtraction is used to extract moving silhouettes of the walker. The...
Face recognition, as one of the most interesting and successful applications of image understanding and machine vision, has grown a lot of attention during the past years. Basically human faces are very similar in structure with minor differences from person to person. In this paper a new robust face recognition method is proposed which exploit edge-based features of faces. The performance of this...
The rapid expansion in the amount of biological data being generated worldwide is exceeding efforts to manage analysis of the data. Annotation can be specified as any piece of information associated with an amino acid sequence. Annotation is a process of relating additional information with a particular point in a piece of information. The present task is completely based on the biological database...
This paper presents advances on the Human ID Gait Challenge. Our method is based on combining an improved gait recognition method with an adapted low resolution face recognition method. For this, we experiment with a new automated segmentation technique based on alpha-matting. This allows better construction of feature images used for gait recognition. The same segmentation is also used as a basis...
In some countries, many problems according to aging are pointed out. Decrease of worker's physical ability is one of them. The old workers have high techniques, but physical ability is lower than that of young workers. And it becomes difficult to keep high quality. Hence it is thought that a power assist by robot is needed. The method that increases human motion simply is mainstream conventional power...
Emotions are an important part of human communication and are expressed both verbally and non-verbally. Common nonverbal vocalizations such as laughter, cries and sighs carry important emotional content in conversations. Sighs often are associated with negative emotion. In this work, we show that emotional sighs exist along both ends of the valence axis (positive-emotion vs. negative-emotion sighs)...
In this paper, a new age estimation framework considering the intrinsic properties of human ages is proposed, which improves the dimensionality reduction techniques to learn the connections between facial features and aging labels. To enhance the performance of dimensionality reduction, a distance metric adjustment step is introduced in advance to achieve a suitable metric in the feature space. In...
This paper describes some of the results from the project entitled “New Parameterization for Emotional Speech Synthesis” held at the Summer 2011 JHU CLSP workshop. We describe experiments on how to use articulatory features as a meaningful intermediate representation for speech synthesis. This parameterization not only allows us to reproduce natural sounding speech but also allows us to generate stylistically...
Multiple research has shown the advantage of patch-based or local representation for face recognition. This paper builds on a novel way of putting the patches in context, using a foveated representation. While humans focus on local regions and move between them, they always see these regions in “context”. We hypothesize that using foveated context can improve performance of local region or patch based...
This paper presents a novel approach to accessing information stored in legacy relational databases (RDB), based on Semantic Web (SW) and multiagent systems (MAS) technologies. Its purpose is to provide the users of enterprise decision-support systems with direct, flexible, and customized access to information, through high-level semantic queries, without the need to modify the underlying legacy databases...
Without a doubt there is emotion in sound. So far, however, research efforts have focused on emotion in speech and music despite many applications in emotion-sensitive sound retrieval. This paper is an attempt at automatic emotion recognition of general sounds. We selected sound clips from different areas of the daily human environment and model them using the increasingly popular dimensional approach...
A new block-based multi-metric fusion (BMMF) approach is proposed for perceptual image quality assessment. The proposed BMMF scheme automatically detects image content and distortion types in a block via machine learning, which is motivated by the observation that the performance of an image quality metric is highly influenced by these factors. Locally, image block content is classified into three...
The development of a hierarchical knowledge map to be used with an intelligent questioning system is described in detail in this paper. The purpose of the intelligent questioning system is to improve the educational process in engineering courses by allowing students to learn more in less time, to understand more deeply, and to enjoy their learning experience. Key elements of this system are a question...
In interactive content search through comparisons, a user searching for a target object in a database is asked to select the object most similar to her target from a small list of objects. A new object list is then presented to the user based on her earlier selections. This process is repeated until the target is included in the list presented, at which point the search terminates. We study this problem...
Human aging face prediction is a popular research topic because of its various useful applications such as security system, missing persons search system, etc. In this study, we propose Exemplar-based Algorithm whose property considers the environment of human growth. Moreover, both the non-negative matrix factorization and linear interpolation methods are used to perform the prediction for six facial...
The block-based multi-metric fusion (BMMF) is one of the state-of-the-art perceptual image quality assessment (IQA) schemes. With this scheme, image quality is analyzed in a block-by-block fashion according to the block content type (i.e. smooth, edge and texture blocks) and the distortion type. Then, a suitable IQA metric is adopted to evaluate the quality of each block. Various fusion strategies...
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