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Striatum is a major stage of the motor loop but, despite a pivotal role in the execution of movements, it has been poorly studied thus far under Parkinsonian conditions and Deep Brain Stimulation (DBS). We propose a computational framework to analyze the spiking activity of striatal neurons under several conditions. This framework combines point process models and single unit recordings, and separately...
Webbles are the most recent form of IntelligentPad. Webbles are objects in a browser window that allow for direct manipulation by drag and drop. One may pick up any Webble and move it over any other one for operational combination. The new Webble is plugged into the previous one and data between them flow through predefined slots. Human users may freely reconfigure the slot connections of Webbles...
We propose a new method for audio-visual sensor fusion and apply it to automatic aggression detection. While a variety of definitions of aggression exist, in this paper we see it as any kind of behavior that has a disturbing effect on others. We have collected multi- and unimodal assessments by humans, who have given aggression scores on a 3 point scale. There are no trivial fusion algorithms to predict...
The difference between interactive evolution-ary computation (IEC) and traditional evolutionary computation (TEC) is that in IEC individuals' fitness is subjectively assigned by the user, while in TEC the fitness is objectively given by function or others. The user in IEC assigns fitness according to his/her preference. Therefore, if his/her preference drifts, the implicit fitness function for preference...
In this paper, we propose a system to collect human behavior in detail with higher-level tags such as attitude, accompanying-person, expenditure, tasks and so on. The system makes it possible to construct database to model higher-level human behaviors that are utilized in context-aware services. The system has two input methods, i.e., on-the-fly by a smart phone and post-processing by a PC browser...
In this paper we propose an approach to recognize human actions using depth images. Here, we capture the motion dynamics of the object from the depth difference image and average depth image. The features from the space-time depth difference images are obtained from hierarchical division of the silhouette bounding box. We also make use of motion history images to represent the temporal information...
This paper presents the definition of a process for performing rework, and a tool that executes the process in order to support humans seeking help in being sure that they are carrying out rework completely and correctly. The process definition treats rework as the reinstantiation of previously-performed activities in new contexts, which requires the careful specification and management of the values...
With the vigorous development of IOT (Internet of Things), sensor units carried by human beings will form the largest DTMSN in the world. However, most of the existing DTMSN routing protocols haven't taken the characteristics of human mobility into account, and may not work well in human-oriented data gathering. In this paper, we analyze the characteristics of human mobility, and propose a novel delay-...
Most human centric business activities, like the handling of an insurance claim or the design of an IT solution, do not follow a formal process model word-by-word. While there are often underlying processes in place, the real business operation typically encompasses a wider scope of actions. It includes unstructured segments of human activities, additional documents and interactions, the integration...
Recent advances in neuroscience and robotics have allowed initial demonstrations of brain-computer interfaces (BCIs) for controlling wheeled and humanoid robots. However, further advances have proved challenging due to the low throughput of the interfaces and the high degrees-of-freedom (DOF) of the robots. In this paper, we build on our previous work on Hierarchical BCIs (HBCIs) which seek to mitigate...
This paper summarizes the recent development of action recognition at first. Then based on Hierarchical Filtered Motion model and Nearest Neighbor classifier, we do action recognition using HOG feature in video sequences of different resolutions. Here we use KTH dataset for training and MSR action dataset II for testing. The experiment demonstrates that the new feature extraction process is effective...
We proposed a model that is capable of handling the patterns of ambiguous recurring tasks. If we can grasp the pattern, it would be useful for prediction of the tasks which might happen in the future, and also be the hint on handing them over to co-workers. To utilize our model, we have developed a concrete method for manipulation or visualization of the modeled data. This method is useful to build...
Situation-aware case-based decision support (SACBDS) systems comprise two distinct parts: situation awareness (SA) and case-based reasoning (CBR). The SA part keeps a finite history of the time space information of the domain and uses rules to interpret cues from the environment with respect to an individual user's context, and then anticipates future situations by performing statistical inference...
This paper proposes a method of motion recognition in real night environment employing an infrared radiation camera. We record a video employing an infrared radiation camera to perform motion recognition at night. We use Directional Motion History Images (DMHIs) and Directional Motion Energy Images (DMEIs) for human motion representation. For the recognition of the motions, we employ the eigenspace...
A meta-model comprising knowledge(K), objectives(Q), resource(R) and locations(L) is proposed as habitat of a person. The model is used for scheduling of person activities to achieve its goal. The activities mainly include knowledge acquisition, resource generation and migration. And the model can also be used to reason on minimal requirements of a person, testing achievement of a goal and deciding...
Web search is a key information retrieval method for human beings in current society, both in the fields of academic and commercial activities. Due to "one-size-fits-all" approach limit to search results obtainment, there are still challenges to give personalized web service with high precision in traditional web search process. Herein, a new framework is proposed to advance traditional...
In this paper, we present a simple yet effective approach to recognizing human activities from video sequences. Our approach integrates the advantages of human action recognition in static images using action key poses and motion based approaches using the variants of Motion History Images (MHI) and Motion Energy Images(MEI). We combine both methodologies to extract a new representation of temporal...
Application address streams contain a wealth of information that can be used to characterize the behavior of applications. However, the collection and handling of address streams is complicated by their size and the cost of collecting them. We present PSnAP, a compression scheme specifically designed for capturing the fine-grained patterns that occur in well structured, memory intensive, high performance...
In this paper, we present a home-monitoring oriented human activity recognition benchmark database, based on the combination of a color video camera and a depth sensor. Our contributions are two-fold: 1) We have created a publicly releasable human activity video database (i.e., named as RGBD-HuDaAct), which contains synchronized color-depth video streams, for the task of human daily activity recognition...
This paper presents a human action recognition method using histogram of oriented gradient (HOG) of motion history image (MHI). First, the proposed method generates MHI with differential images which are obtained by frame difference of successive frames of a video. The histogram of oriented gradient (HOG) of the MHI is then computed. Finally, support vector machine (SVM) is applied to train an action...
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