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A system for humanoid robot arm movement concerns about generating a human-like point-to-point (p2p) trajectory. For more than a decade, numerous systems have been devised and many of them were based on complex dynamical systems. In this paper, we introduce a simpler system, integrating support vector machine (SVM) learning model, which can achieve same p2p objective. In our experiment, we compare...
Detecting lies is crucial in many areas, such as airport security, police investigations, counter-terrorism, etc. One technique to detect lies is through the identification of facial micro-expressions, which are brief, involuntary expressions shown on the face of humans when they are trying to conceal or repress emotions. Manual measurement of micro-expressions is hard labor, time consuming, and inaccurate...
This paper proposes a system to recognize quasi-periodic human actions from monocular video sequences. First, each input video frame is analyzed and estimated to generate the best 3D human model pose which consists of a set of 3D coordinates of specific human joints. Next, these 3D coordinates for each frame are converted into corresponding 3D geometric relational features (GRFs), which describe the...
This paper presents a Nonlinear AutoRegressive with eXogenous input (NARX)-based approach for human-emotion recognition from an input video. The dynamics of facial expressions are first captured by performing a temporal-spatial analysis by extracting local and spatial features using a pyramid of histograms of oriented gradients (PHOG) descriptor. Then the temporal phases of facial expressions are...
A benchmark evaluation dataset which reflects users' search behaviors in the real world is indispensable for evaluating the performance of information retrieval applications. A typical evaluation dataset consists of a document set, a topic set and relevance judgments. Manual preparation of an evaluation dataset needs much human cost, and human-made topics may not fully capture users' real search needs...
Acoustic Resonance Testing (ART) is a nondestructive test that uses the vibrational characteristics of an object to find defects. It is a whole-part test, so measurements taken in one place can indicate defects anywhere. It can be done quickly and requires minimal equipment. ART can be completely automated and make objective, quantitative judgments, eliminating human error. ART uses the fact that...
This work investigates a semantic-driven human detection algorithm, which employs global human template matching to inspire the local features based Adaboosting algorithm. We use distance transform to analyze distances between training samples and human contour template to obtain a classifier based on human outline features. At the training stage, the global outline feature will be coordinated into...
Advancements in Service-Oriented Architectures, Cloud Computing and Wireless Sensor Networks pose challenges with respect to dynamic application adaptation, the ability to reconfigure applications so as to support continuous, unimpeded augmentation of services in response to changing environmental circumstances. Proactivity of Service Based applications refers to anticipatory, change-oriented and...
Advanced Driver Assistant Systems act, by definition in natural, often poorly structured, environments and are supposed to closely interact with human operators. Both, natural environments as well as human behaviour have no inherent metric and can not be modelled/measured in the classical way physically plausibly behaving systems are described.
Unit testing of legacy code is often characterized by the goal to find a maximum number of defects with minimal effort. In context of restrictive time frames and limited resources, approaches for generating test cases promise increased defect detection effectiveness. This paper presents the results of an empirical study investigating the effectiveness of (a) manual unit testing conducted by 48 master...
This research work proposes an innovative processing scheme for the exploitation of eye movement dynamics on the field of biometrical identification. As the mechanisms that derive eye movements highly depend on each person's idiosyncrasies, cues that reflect at a certain extent individual characteristics may be captured and subsequently deployed for the implementation of a robust identification system...
Pedestrian detection is a major difficulty in the field of object detection. In order to achieve a balance between speed and accuracy, we propose a new framework in pedestrian detection based on HOG-PCA and Gentle AdaBoost. Firstly, each block-based feature of the image is encoded using the histograms of oriented gradients (HOG), then Principal Components Analysis (PCA) is used to reduce the dimensions...
Text Summarization is the process of identifying and extracting the most vital information in a document. It has been seen as an effective method for dealing with increasing amount of information on the Internet nowadays. In this paper, we present an application of Genetic Programming to the problem of Automatic Text Summarization. Genetic Programming was used to evolve the function that ranks the...
Websites serve as the presenting carriers for excellent courses construction. With the deepening of excellent courses construction and research, we have relinquished the pure evaluating display platform, and constructed comprehensive courses websites combined with teaching applications, management and display. The practice has become a tendency for the construction of excellent courses websites. In...
In this paper, we present a driver-automation system for providing brake assistance to the driver using the concepts of various levels of intervention. The system offers potential for further development and integration into main stream cars using by-wire technology, both from passenger safety and system usability perspectives. The criticality of the situation of a potential crash is estimated using...
This fast abstract outlines a novel mechanism for monitoring the security state of a system, using intelligent testing agents to instigate and then depress security activities.
The need for early detection of temporal events from sequential data arises in a wide spectrum of applications ranging from human-robot interaction to video security. While temporal event detection has been extensively studied, early detection is a relatively unexplored problem. This paper proposes a maximum-margin framework for training temporal event detectors to recognize partial events, enabling...
Intention recognition plays a key role in the cooperation among the humans. An intention describes an action or sequence of actions to be performed for achieving the intended purpose. The cooperating humans learn each others intentions while cooperation. In this paper we propose three ways how a robot can learn the intention of the cooperating human. In the first case, the robot learns the human intention...
A conceptual framework is proposed to examine perceived structural constraints of elephant conservation centre and its' effects on participation in visiting activity. A brief discussion on elephant conservation effort is discussed in the earlier part of this paper. The paper then examines some attributes to perceive structural constraints with some effects are examined for participation and overall...
Insight into brain development and organization can be gained by computing correlations between structural and functional measures in parcellated cortex. Partial correlations can often reduce ambiguity in correlation data by identifying those pairs of regions whose similarity cannot be explained by the influence of other regions with which they may both interact. Consequently a graph with edges indicating...
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