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Three-dimensional (3D) anthropometry can provide rich shape information and will contribute fundamental part of many anthropometric, biological, anthropological, archaeological and botanical researches, etc. In this paper, typical challenges in the application of 3D anthropometry are highlighted, e.g. automatic landmark identification from 3D anthropometric data, shape comparison and analysis by using...
We present an effective real-time approach for automatically reconstructing 3D human body poses from monocular video sequences. In this approach, human body is automatically detected from video sequence, then image features such as silhouette, edge and color are extracted and integrated to infer 3D human poses in an iterative way by minimizing the cost function defined between 2D features from the...
In this paper, we present a novel framework to recover human body pose on multi camera systems. Our framework leverages 3D voxel data, which are reconstructed from multi-camera systems. The use of voxel data leads to viewpoint-free estimation, which benefits in that reconstruction of a training model is needless in different multi-camera arrangements. Other notable aspects of our approach are real-time...
In this paper, we present an approach to capture markerless human motion and recognize human poses. Different body parts such as the torso and the hands are segmented from the whole body and tracked over time. A 2D model is used for the torso detection and tracking, while a skin color model is utilized for the hands tracking. Moreover, 3D location of these body parts are calculated and further used...
A reliable model-based human motion tracking scheme is presented. In this approach, silhouette image sequences from a top-view camera and a side-view camera work together to track human motion in 3D space in real time. The adoption of one top view camera introduces many attractive characteristics. A convenient calibration scheme is presented by decoupling different camera parameters to the largest...
In this paper, we suggest a new method of vision-based human augmented mapping for indoor environments. It is a semi-autonomous approach using human-robot interation and can be an alternative to autonomous map building. The advantage of our approach is that the user can share the environments with the robot and insert semantic information to the environmental map. We apply PCA features for visual...
In networked virtual environments, videoconferences or chatting over the Internet users are often graphically represented by virtual characters. Modeling realistic virtual heads of users suitable for animation implies a heavy artistic effort and resource cost. This paper introduces a system that generates a 3D model of a real human head with a little human intervention. The system receives five input...
In this paper, novel 2 one-dimensional (1D) Haar-like filtering techniques are proposed as a new and low calculation cost feature extraction method suitable for 3D acceleration signals based human activity recognition. Proposed filtering method is a simple difference filter with variable filter parameters. Our method holds a strong adaptability to various classification problems which no previously...
The establishment of the likelihood model of state observation with a strong robustness is one of the core issues in the study of moving hand tracking. This paper is dedicated to building a robust likelihood model of state observation, and do some study by using the method of gaining feature points from frame images of human hand. Firstly, based on physiological models and camera projection principle,...
Human hand gesture features extraction from the frame image sequences is one of the key jobs in the process of human hand tracking based upon particle filtering (PF), because it provides PF with key data for computing the weight value of a particle. In order to satisfy the need of real time human hand tracking, a novel features extraction approach, aimed at optimization of processing speed, is put...
In this paper, we present an efficient discriminative method for human pose estimation. This method learns a direct mapping from visual observations to human body configurations. The framework requires that the visual features should be powerful enough to discriminate the subtle differences between similar human poses. We propose to describe the image features using salient interest points that are...
In this paper, we propose a method to estimate the 3D human posture from monocular image without using the markers. A 3D human body is expressed by a multi-joint model, and a set of the joint angles describes a posture. The proposed method estimates the posture using histograms of oriented gradients(HOG) feature vectors that can express the shape of the object in the input image obtained from monocular...
In this paper, we present a novel method for human action recognition with the combined global movement feature and local configuration feature. The human action is represented as a sequence of joints in the 4D spatio-temporal space, and modeled by two HMMs, a conventional HMM for global movement feature and an exemplar-based HMM for configuration feature. Firstly, an adaptive particle filter is adopted...
A new approach to modelling and classification of human gait is proposed. Body movements are obtained using a sensor suit that records inertial signals that are subsequently modelled on a humanoid frame with 23 degrees of freedom (DOF). Measured signals include position, velocity, acceleration, orientation, angular velocity and angular acceleration. Using a range of concurrent features extracted from...
In this paper we propose a new geometric method for 3D face recognition based on anthropometric measurements. 3D facial feature points are measured by stereovision and are used to construct a 3D signature containing distances, indices and angles between these points, in order to discriminate individuals. This approach is evaluated on the new IV2 database and results are presented an discussed.
We have presented motion history-based human motion recognition technique with various formats of feature vectors. Since the inception of the motion history image (MHI) template for motion recognition, various progresses have been adopted to improve this basic MHI. Stages of development of appearance-based representation and recognition approach are presented here on the basic motion history-based...
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information complexity criterion to identify discriminant feature-clusters of lower dimensionality. We apply this framework on human face anthropometry data of 32 features collected from each of the 300 3D face mesh models. The feature-subsets...
This paper investigates a human body posture estimation method based on the back projection of human silhouette images extracted from multi-camera images. The multi-camera system is based on a server-client system with local network of 1000 Base-T to achieve a voxel 3D reconstruction of human body posture in real-time. In order to extract significant points of the human body such as head, neck, shoulders,...
In this paper, we discuss a robot vision in order to perceive people and the environment around a mobile robot. We developed a tele-operated mobile robot with a pan-tilt mechanism composed of a camera and a laser range finder (LRF). In this paper, we propose a method for sensor fusion to extract a human from the measured data by integrating these outputs based on the concept of synthesis. Next, we...
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