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Nowadays, a lot of attention has been focused on developing human motion analysis system for sport science application. With the advance computational power and speed, computer researchers are now able to develop markerless human motion analysis instead of placing special markers and sensors onto the test subject. Our research focuses on tracking the major body of a professional golfer directly from...
Researchers in the area of neuroscience, psychophysiology and communication technology believe that emotion plays an important role in decision making, learning and memory. Recent years, due to the development of instrument and experimental paradigm, emotion and its' influence on decision making has become clear. This paper utilized Iowa Gambling Task (IGT) and Heart Rate Variability (HRV) analysis,...
This paper proposes a particle filter based marker-less upper body motion capture system, capable of running in realtime. This system is designed for a humanoid robot application, and thus a monocular image sequence is used as input. We first set up a model of the human body, a sub-model which includes 11 Degrees of Freedom is used for the upper body tracking. Considering the realtime processing requirements,...
This paper presents an approach for markerless vision-based motion capture from multiple views. We use truncated cones to describe the human body parts, and match the extremal contours of human body model against the image cues. Because the derivative is not available, we assume that the cost function satisfies a quadratic model inside the trust region and use model-based Derivative Free Optimization...
In this paper, we propose a rule-based system for semantically understanding and analyzing the motion of the trajectories of the human activity. The proposed system can be used as a preprocessing phase for enhancing the object detection process. Detected trajectories are classified into three categories; normal, semi-normal and abnormal trajectories according to the distances between their adjacent...
Human-robot interaction is necessary in remote teleoperation of robot manipulators, especially when the environment is unstructured and objects are unfamiliar. In traditional interactive methods using contacting mechanical devices, the motion of the operator is restricted and unnatural. While camera-based tracking has the benefit of being non-contact, previous vision-based approaches have used only...
We propose a new Particle Filter (PF) based Particle Swarm Optimization (PSO) algorithm for 3D articulated human pose estimation. The sampling covariance and annealing factor items are incorporated into the velocity updating equation of PSO, which are initiated with appropriate values at the beginning of PSO iteration, and decreasing (`annealed') by reasonable steps. The new algorithm can, in some...
This paper presents a new application that aims at improving communication and interactions between digital media and customers at a point of sale. Our system analyzes in real-time human behaviour while shopping. In particular, the system detects customer's interest in products and interaction such as people grabbing products. This system is based on a behaviour model. A video analysis module detects...
Motion Tracking has been applied in many recent applications like surveillance, advance driver assistance system (ADAS), non-cooperative biometrics, virtual reality, etc. Current research in this field includes making tracking system more robust and reliable. Imaging modality to be used in motion tracking also includes thermal imaging (FIR) in addition to the visible imaging. We propose here a motion...
Human detection and tracking is a task common to many applications, such as video surveillance and security, intelligent vehicles, safety driving, public security, etc. Histogram of oriented gradient (HOG) gives an accurate description of the contour of human body. Based on HOG and support vector machine (SVM) theory, a classifier for pedestrian is obtained. The classifier is then used to find the...
Many state of the arts latent models have been investigated to learn different latent variables with Gaussian processes models (GPs). However, seldom research focus on a shared latent dynamical model (SLDM) of GPs and its application in a high dimensional nonlinear system. In this paper, we propose a shared latent dynamical model, which combines the idea of GPDM with SLS, and give its application...
In this paper, we introduce a novel method to detect a carried object seen from a stationary camera using human body silhouette feature information. We use star skeletonization technique with the adaptive centroid point to extract human feature. The carried object is classified using time series of motions of the extracted skeleton limbs. The boundary of the carried object is figured from carried...
Laser range finders are a non-invasive tool which can be used for anonymously tracking the motion of people and robots in real-world environments with high accuracy. Based on a commercial system we have developed, this paper addresses two practical issues of using networks of portable laser range finders in field environments. We first describe a technique for automated calibration of sensor positions...
This paper presents an upper body tracking algorithm with a single monocular camera. In order to be suitable for human robot interaction, the designed method should be free to work on the moving camera platform and also can achieve real-time performance. The dimension of human posture model is extremely high, and we hereby focus on the visual extraction of head and arms. A hierarchical structure model...
In this paper, we propose a marker-less full body human motion capture system designed for humanoid robot applications. The system is based on a stereo camera, and therefore has strong portability. Tracking is implemented within the particle filter framework, and the high dimensionality problem is solved through partitioned sampling. Taking advantage of the stereo setup, we propose a depth cue which...
Human robot interaction is an emerging area of research with many challenges. Knowledge about human behaviors could lead to more effective and efficient interactions of a robot in populated environments. This paper presents a probabilistic framework for the learning and representation of human motion patterns in an office environment. It is based on the observation that most human trajectories are...
This paper presents an efficient method for monocular recovering and tracking 3D human pose using 3D to 2D joints correspondences. Different from previous work, its main novelty lies in several aspects: Firstly, our method does not involve any complex features, which means that it does not tend to rely on good foreground segmentation. Secondly, formulating the model as an second order cone programming...
Nowadays, face recognition algorithms, proposed in the literature, reached a correct performance level when the acquisitions conditions for the tested images are controlled (variability of the environment, illumination, poses, expressions and also the number of images in the database to identify people). These performances fall when these conditions are degraded. The controlled conditions of acquisition...
This work is a status report of the job in progress finalized to the estimation of the dose distribution inside the head of a patient undergoing a high resolution CT (Computed Tomography) for the diagnosis of pathologies related to the inner ear. Geant4 (GEometry ANd Tracking) has been used to simulate the head and propagate the particles in the human tissues. The ear has a very complex structure,...
We propose a simple and efficient online strategy based on inertial sensors to follow human arm movements in the task space by robotic platforms. The strategy is composed by the following ingredients: 2 inertial sensors attached to the human arm and forearm, the differential kinematics (DK) as well as the dynamic model of the corresponding robot and a motion control scheme. We use inertial sensors...
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