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This paper proposes an investigation on classification of the positive and negative emotions via the use of electroencephalogram (EEG). EEG bandpowers are extracted as the feature of interest. Two simple decision rules to classify positive and negative emotions are proposed, i.e. 1) using both the left and right frontal information and 2) using only one side of the left or right frontal information...
It has been a decade since the Workshop on Grand Challenge for Modeling & Simulation (M&S) was held at Dagstuhl in Germany (www.dagstuhl.de/02351). Grand challenges provide a critical focal point for research and development and can potentially create the critical mass needed to bring substantial transformation and benefit to a community. The Workshop addressed a wide variety of M&S theoretical,...
Smart vehicle technologies such as ADAS are growing concern about. Especially, pedestrian and vehicle recognition system based on machine vision is a big issue. In this paper, we propose the hardwired HOG feature extractor circuit for real-time human and vehicle detection, and describe the hardware implementation results. Our HOG feature extractor supports weighted gradient value, 2D histogram interpolation...
Future urban computing scenarios will be characterized by the close integration of ICT devices and humans. Citizens, by using their own capabilities augmented and integrated with ICT technologies, could thus collaboratively realize a sort of socio-technical super organism to support high-levels of collective "urban" intelligence and various forms of collective actions. This position paper,...
This paper presents a unified action recognition framework combining harris3D descriptor with 3D SIFT detector. We perform action recognition experiments on the KTH dataset using Support Vector Machines. Experiments apply the leave-one-out and compare our proposed approach with state-of-the-art methods. The result shows that our proposed approach is effective. Compared with other approaches our approach...
Software developers have long been supported by a variety of tools, such as version control systems (e.g., GIT), issue tracking systems (e.g., BugZilla), and mailing list services (e.g., Mailman). These tools accumulate a wide range of information that is recorded in the repositories these tools store their data in. This information is comprised of two significantly different types of data: structured...
Pose tracking technique has great potential for many applications such as marker-free human motion capture system, Human Computer Interactions (HCI), and video surveillance. Though many methods are introduced during last decades, self-occlusion - one body part is occluded by another one - is still considered one of the most difficult problems for 3D human pose tracking. In this paper, we propose a...
In human body pose estimation, manifold learning is a useful method for reducing the dimension of 2D images and 3D body configuration data. Most commonly, body pose is estimated from silhouettes derived from images or image sequences. A major problem when applying manifold estimation, however, is its vulnerability to silhouette variation. In this paper, we propose a novel approach to solving viewpoint-induced...
Telexistence technology enables a highly realistic sensation of existence in a remote place without any actual travel. The concept was originally proposed by the first author in 1980, and its feasibility has been demonstrated through the construction of alter-ego robot systems such as TELESAR & TELESAR V, which were developed under the national large scale project on “Robots in Hazardous Environments”...
The prospect of controlling devices merely by the power of one's thoughts is compelling, especially for assistive technology applications. In the accompanying video, we show how we have strived to push brain-computer interface (BCI) technology out of the lab and into the real world, while simultaneously moving away from testing solely with healthy subjects to undertaking trials with patients and potential...
We present results from a web-based experiment conducted to assess the effect of Twitter metadata on decision making in content consumption. Participants were presented with information concerning two tweets and asked which they would prefer to read. Analysis of the results shows that recognition of the author as being within the readers local network is highly influential in the decision to read...
DNA sequencing technology has advanced to a point where storage is becoming the central bottleneck in the acquisition and mining of more data. Large amounts of data are vital for genomics research, and generic compression tools, while viable, cannot offer the same savings as approaches tuned to inherent biological properties. We propose an algorithm to compress a target genome given a known reference...
In this doctoral consortium paper I describe the theme of my research, the model-based generation of consistent emotional turn taking behavior in virtual human conversations and the evaluation of this behavior. My goal is to investigate and generate convincing social behavior in embodied conversational agents.
The Web is an evolving, complex socio-technical system. As a social technology, the Web is a diverse collection of interacting networks of activities and communities. The openness and scalability of the Web has provided a platform for new technologies, services and standards, enabling individuals at scale to connect, communicate and share in ways that were previously impractical. The Web has enabled...
In this article we introduce the C-Model of Interaction between humans and Digital Media1 we empirically researched and analyzed in learning scenarios (workshops). In our trienal research project called “Subject Formation and Digital Culture” (SKUDI) we arranged and designed a series of constructivist and constructionist workshops. In these workshops dealing with robots, smart textiles, fabrication...
While the analysis of online social networks is a prominent research topic, offline real-world networks are still not covered extensively. However, their analysis can provide important insights into human behavior. In this paper, we analyze influence factors for link prediction in human contact networks. Specifically, we consider the prediction of new links, and extend it to the analysis of recurring...
In the field of video surveillance, multiple object tracking is a challenging problem in the real application. In this paper, we propose a multiple object tracking method by spatiotemporal tracklet association. Firstly, reliable tracklets, the fragments of the entire trajectory of individual object movement, are generated by frame-wise association between object localization results in the neighbor...
Often the AI techniques for decision making used in commercial games are predictable and unadaptive. Arguably, this causes a lack of realism for the players. We believe that emotions are a vital part in the creation of interesting and believable non-player characters for games. In this paper, we present an extension to behavior trees that incorporates emotions into the decision making. Specifically,...
We present the huddle, a concept for extending games in which the player is responsible for a group of game characters. The huddle combines several AI methods to allow the player to create a cooperative strategy for his characters to solve a scenario of the game and it takes away from the player the need to frantically jump around in controlling his characters to employ the strategy idea he has. The...
The temporal annotation scheme Time ML was developed to support research in complex temporal question answering (QA). Given the complexity of temporal QA, most of the efforts have focused, so far, on extracting temporal information, which has been evaluated with corpus-based evaluation. However, the QA task represents a natural way to evaluate temporal information understanding, and creating question...
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