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Human activity recognition has potential to impact a wide range of applications from surveillance to human computer interfaces to content based video retrieval. Recently, the rapid development of inexpensive depth sensors (e.g. Microsoft Kinect) provides adequate accuracy for real-time full-body human tracking for activity recognition applications. In this paper, we create a complex human activity...
Understanding natural human activity involves not only identifying the action being performed, but also locating the semantic elements of the scene and describing the person's interaction with them. We present a system that is able to recognize complex, fine-grained human actions involving the manipulation of objects in realistic action sequences. Our method takes advantage of recent advances in sensors...
Affective, ‘emotional’ as widely known, gaming, constitutes the new frontier for game design and development. The ultimate goal is being able to read the emotional state of a gamer and use it to change the game in such a way so as to provide to him/her a more immersive experience, a better gameplay. However, existing affective gaming approaches use specialized sensors in order to extract behavioral...
Dextrous object manipulation with multi-fingered robot hands remains one of the key challenges of service robotics. So far, most theoretical approaches and simulators have concentrated on the search for and evaluation of static stable grasps, but with neither a model of the full hand-arm system nor the system dynamics. GraspIt! is probably the best-known simulator of this kind.
Understanding and modeling of welder response to 3D weld pool surface help develop intelligent welding robotic systems and better train welders. In this paper, a welder's adjustment on the welding current as a response to the 3D weld pool surface as characterized by its width, length, and convexity is studied. A vision sensing system is developed to real-time measure the specular 3D weld pool in gas...
This study investigates and acts as a trial clinical outcome for human motion and behaviour analysis in consensus of health related quality of life in Malaysia. It was developed to analyse and access the quality of human motion that can be used in hospitals, clinics and human motion researches. It aims to establish how widespread the quality of life effects of human motion. Reliability and validity...
Since the birth of Intrusion Detection System (IDS) technology, the most significant implementation problem is the enormous number of alerts generated by the IDS sensors. Moreover due to this obtrusive predicament, two other problems have emerged which are the difficulty in processing the alerts accurately and also the decrease in performance rate in terms of time and memory capacity while processing...
Human activity recognition using wearable body sensors is playing a significant role in ubiquitous and mobile computing. One of the issues related to this wearable technology is that the captured activity signals are highly dependent on the location where the sensors are worn on the human body. Existing research work either extracts location information from certain activity signals or takes advantage...
Compressive Sensing (CS) theory has gained widespread attention due to its advantage of breaking through the limits of Nyquist sampling theorem. To make the CS more adaptive, some works based on the human vision system (HVS) have been conducted, but incurring some other problems at the same time, such as additional sensors, higher computation power and added experiments. To solve these problems a...
People-centric participatory sensing empowers people to collect and share sensor data using mobile devices across many applications. These people-centric services utilize a client-server architecture to provide meaningful information to different participating people. In this paper we present the COSN framework that provides people-centric services without relying on an infrastructure and dedicated...
We live in an era where billions of computers are interconnected. In the very near future, not only computers but also many different digital devices and other physical objects will be seamlessly connected to each other and be able to communicate with little or no human intervention. These interconnected objects are called smart devices, and this concept is called Internet of Things. In this paper,...
We present here preliminary findings from our ongoing study of situation awareness in cybersecurity (cyber-SA). Analysis of data collected from the field has produced two preliminary findings. One, cyber-SA is distributed across individuals, technological agents, and functional domains. Two, an absence of effective boundary objects inhibit cross-boundary collaboration and reduce individual cyber-SA.
Some home monitoring research has tried to deal with a broad range of human behaviors such Activity of Daily Living (ADL) or Instrumented ADL (IADL) in an entire home, but most research results does not yet seem satisfactory. So we focused on modeling human behaviors in a bedroom, not an entire home. To do this, we define a behavior state and behaviors. We constructed the experimental system by installing...
We present the framework design and modeling for an integrated vehicular and human-centric urban sensing system. The goal is to understand the impact of vehicles and human activities on the surrounding environment. This is achieved through a seamless integration of the human aspect into vehicular and urban sensing going beyond the traditional human-in-the-loop sampling methodologies. We describe the...
A human activity representation method based on event histogram was put forward, and the human activity recognition was realized based on event histogram and KL transform. Ubiquitous sensors were used to acquire data and based on these data human recognition was realized. In order to model the sensor data sequences, the concept of event and event histogram was put forward. The event is corresponding...
An adaptive synergy controller is presented which autonomously modulates the finger synergies of a dexterous robotic hand according to the relative orientation of a grasped object. The adaptive synergy controller is derived from approximating the human motion of unscrewing a bottle cap with sinusoids to replicate the task with a robotic hand. In preliminary experiments, the finger joint motions of...
Estimation of human motion has been improved by recent advances in depth sensors such as the Microsoft Kinect. However, they often have limited range of depths and a large number of such sensors are necessary to estimate motion in large areas. In this paper, we explore the possibility of estimating motion from monocular data using initial and intermittent 3D models provided by the depth sensor. We...
This paper tackles a challenging problem of inertial sensor-based recognition for similar walking action classes. We solve two remaining problems of existing methods in the case of walking actions: action signal segmentation and recognition of similar action classes. First, to robustly segment the walking action under drastic changes such as speed, intensity, or style, we rely on the likelihood of...
The use of wearable sensors for human activity monitoring and recognition is becoming an important technology due to its potential benefits to our daily lives. In this paper, we present a sparse representation-based human activity modeling and recognition approach using wearable motion sensors. Our approach first learns an overcomplete dictionary to find the motion primitives shared by all activity...
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