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Computerized human face recognition is a complex task of deformable pattern recognition. The principal source of complexities lies in the significant inter-class overlapping of faces due to the variations caused by different poses, illuminations, and expressions (PIE). The popularly used computerized face recognition algorithms like PCA, EBGM etc. are fairly reliable to determine facial attributes...
This project deals with overcoming the limitations of the SIFT matching algorithm. We propose a novel way of taking the strengths of the SIFT algorithm and removing the underlying weaknesses to improve SIFT matching in pose variation. This is done by increasing the size of the search database to a certain degree of acceptance. In our bid to improve SIFT matching we have come up with an algorithm to...
It Kokoro means, “heart” in Japanese. It also means “mind”, “soul”, “sensibility”, “wishes” and “sentiments”. All of these belong to the wide range of emotions and concepts that define the complex human condition. To be influenced by emotions is intrinsic to a human being. Emotions arise from having to face up to a changing and partially unpredictable world. This makes it necessary for all intelligent...
Lifelog research often needs collaboration from many disciplines. Also most related works need very advanced expertise while chances to find all skilled members at one place are very rare. It also involves privacy and/or copyrighted materials where the mutual consent of the use of data is very important. Thus a secure Web-based service is a great way for researchers for technical collaboration to...
This research reports the development and evaluation of Malay emotional voice corpora through listening evaluation, and how the numbers of emotion choices offered to evaluators affect the result of the evaluation. The voice corpora comprises of three emotions, namely anger, sadness and happiness being expressed by two male and two female actors. The voice corpora were evaluated in two separate listening...
Identifying and locating oneself in different hallways of high rise buildings forms the classic indoor localization problem. GPS does not work indoors and WiFi may not be omnipresent. This paper presents a novel approach to ambient magnetic fields based indoor localization. We present a system that classifies magnetic signatures using dynamic time warping. Specifically, by aligning similar magnetic...
The society's concern about safety is growing every day and with it the demand for intelligent surveillance systems with the minimal human intervention possible. In this work we identify suspicious events that could take place in a parking lot based on infrared imagery. The object segmentation process is performed using a dynamic background-subtraction technique which robustly adapts detection to...
A variety of systems exist in which annotations are available at various levels of granularity to a reference coordinate system, such as roads and landmarks on a map, features within a 2-dimensional or 3-dimensional image, or genetic entities (GEs) mapped to a reference genome. As the number of annotations grows, methods to efficiently locate overlapping entities within a specific interval of interest...
Human Speech conveys speaker's emotional state along with linguistic intelligence. Meaning of a speech sample changes when it is uttered with different emotions. The present paper gives a description of different types of studies conducted to analyze, perceive and recognize commonly occurring emotions in Hindi speech. These have been classified as anger, happiness, fear, sadness, surprise in addition...
Social signal processing has the ambitious goal of bridging the social intelligence gap between computers and humans. Nowadays, computers are not only the new interaction partners of humans, but also a privileged interaction medium for social exchange between humans. Consequently, enhancing machine abilities to interpret and reproduce social signals is a crucial requirement for improving computer-mediated...
In this work, we present a Hidden Markov Model (HMM) based stylistic walk synthesizer, where the synthesized styles are combinations or exaggerations of the walk styles present in the training database. In a first stage, Hidden Markov Models of eleven different styles of gait are trained, using a database of motion capture walk sequences. In a second stage, the probability density functions inside...
The main tasks of ground surveillance radars for security and perimeter protection are detection and classification of moving ground targets. In typical radar systems, target detection is fully automated, but the target classification requires human involvement. In this paper, we consider received radar echoes data of ground moving targets, and corresponding signals using cepstrum coefficients. The...
In this work, we explore context-aware application scenarios that become possible utilizing semantically-rich information derived from real-world mobility and presence traces. Traces produced by people carrying personal mobile devices, capturing social and contextual interactions, serve as enables for Future Internet applications. We discuss the fundamental concepts, technical issues and related research...
Supervisory Control and Data Acquisition(SCADA) systems are deeply ingrained in the fabric of critical infrastructure sectors. These computerized real-time process control systems, over geographically dispersed continuous distribution operations, are increasingly subject to serious damage and disruption by cyber means due to their standardization and connectivity to other networks. However, SCADA...
Threat trees are notable tools in the security analysis process called "threat modeling"'. The trees are used to identify how and under what condition threats can be realized, which will help proper estimation of risks and planning of countermeasures. However, it is difficult for an average analyst to construct adequate trees, because security expertise, particularly from an attacker's perspective,...
We study embodiment-specific robot grasping tasks, represented in a probabilistic framework. The framework consists of a Bayesian network (BN) integrated with a novel multi-variate discretization model. The BN models the probabilistic relationships among tasks, objects, grasping actions and constraints. The discretization model provides compact data representation that allows efficient learning of...
Recognizing human activities from common color image sequences faces many challenges, such as complex backgrounds, camera motion, and illumination changes. In this paper, we propose a new 4-dimensional (4D) local spatio-temporal feature that combines both intensity and depth information. The feature detector applies separate filters along the 3D spatial dimensions and the 1D temporal dimension to...
Captured human motion data are used so that humanoid robots or computer graphics (CG) characters can behave naturally. Because the motion capture system is expensive, and time-consuming process is needed to acquire motion data, technology that enables to reuse existing motion data efficiently is required. This paper proposes motion retrieval method with natural language word based on stochastic correlation...
The process of automatic identification or verification of the human face is a very interesting problem in both sociology and industry. The way of gathering biometric information is non intrusive and easy to perform. Systems that can scan faces in big public places like the airport in search of the offender's face are becoming more and more popular. This paper studies the use of the modified Toeplitz...
In this paper we propose a new method for 3D facial expression recognition. We make use of the Zernike moments, which are calculated in the depth image of a 3D facial point cloud. Combining, the Zernike moments along with the 3D point clouds and the depth images, we succeed in tackling problems arising in facial expression recognition due to affine transformations of the data, such as translation,...
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