Towards real-time body pose estimation for presenters in meeting environments

This paper describes a computer vision-based approach to body pose estimation.\ud The algorithm can be executed in real-time and processes low resolution,\ud monocular image sequences. A silhouette is extracted and matched against a\ud projection of a 16 DOF human body model. In addition, skin color is used to\ud locate hands and head. No detailed human body model is needed. We evaluate the\ud approach both quantitatively using synthetic image sequences and qualitatively\ud on video test data of short presentations. The algorithm is developed with the\ud aim of using it in the context of a meeting room where the poses of a presenter\ud have to be estimated. The results can be applied in the domain of virtual\ud environments

Model figging of articulated objects

本稿では人体や手などに代表される多関節物体の三次元姿勢を画像から推定するモデルフィッティングの技術についてサーベイする。画像によるモデルフィッティングの枠組みを,1)推定に利用される画像特徴,2)画像と照合するモデルの表現と照合のパラメータ空間,3)照合時の評価関数と最適解の探索手法,にわけて多関節物体の三次元姿勢推定に特徴的な要素を上記三つの観点から比較整理することを試みる。In this paper, we present a survey report for the model fitting method to estimate3-D posture of articulated objects such as human body and hand. We decompose the model fitting framework into the following threee lements: 1)image feature, 2)model description and parameter space for model-image matching and 3)matching function and its optimization. From the viewpoint of these three issues, we try to compare the various methods of model fitting to each other and summarize them

Tracking and indexing of human actions in video image sequences

Master'sMASTER OF ENGINEERIN

Active modelling of virtual humans

This thesis provides a complete framework that enables the creation of photorealistic 3D human models in real-world environments. The approach allows a non-expert user to use any digital capture device to obtain four images of an individual and create a personalised 3D model, for multimedia applications. To achieve this, it is necessary that the system is automatic and that the reconstruction process is flexible to account for information that is not available or incorrectly captured. In this approach the individual is automatically extracted from the environment using constrained active B-spline templates that are scaled and automatically initialised using only image information. These templates incorporate the energy minimising framework for Active Contour Models, providing a suitable and flexible method to deal with the adjustments in pose an individual can adopt. The final states of the templates describe the individual’s shape. The contours in each view are combined to form a 3D B-spline surface that characterises an individual’s maximal silhouette equivalent. The surface provides a mould that contains sufficient information to allow for the active deformation of an underlying generic human model. This modelling approach is performed using a novel technique that evolves active-meshes to 3D for deforming the underlying human model, while adaptively constraining it to preserve its existing structure. The active-mesh approach incorporates internal constraints that maintain the structural relationship of the vertices of the human model, while external forces deform the model congruous to the 3D surface mould. The strength of the internal constraints can be reduced to allow the model to adopt the exact shape of the bounding volume or strengthened to preserve the internal structure, particularly in areas of high detail. This novel implementation provides a uniform framework that can be simply and automatically applied to the entire human model

A Study on Human Motion Acquisition and Recognition Employing Structured Motion Database

九州工業大学博士学位論文 学位記番号:工博甲第332号　学位授与年月日:平成24年3月23日1 Introduction||2 Human Motion Representation||3 Human Motion Recognition||4 Automatic Human Motion Acquisition||5 Human Motion Recognition Employing Structured Motion Database||6 Analysis on the Constraints in Human Motion Recognition||7 Multiple Persons’ Action Recognition||8 Discussion and ConclusionsHuman motion analysis is an emerging research field for the video-based applications capable of acquiring and recognizing human motions or actions. The automaticity of such a system with these capabilities has vital importance in real-life scenarios. With the increasing number of applications, the demand for a human motion acquisition system is gaining importance day-by-day. We develop such kind of acquisition system based on body-parts modeling strategy. The system is able to acquire the motion by positioning body joints and interpreting those joints by the inter-parts inclination. Besides the development of the acquisition system, there is increasing need for a reliable human motion recognition system in recent years. There are a number of researches on motion recognition is performed in last two decades. At the same time, an enormous amount of bulk motion datasets are becoming available. Therefore, it becomes an indispensable task to develop a motion database that can deal with large variability of motions efficiently. We have developed such a system based on the structured motion database concept. In order to gain a perspective on this issue, we have analyzed various aspects of the motion database with a view to establishing a standard recognition scheme. The conventional structured database is subjected to improvement by considering three aspects: directional organization, nearest neighbor searching problem resolution, and prior direction estimation. In order to investigate and analyze comprehensively the effect of those aspects on motion recognition, we have adopted two forms of motion representation, eigenspace-based motion compression, and B-Tree structured database. Moreover, we have also analyzed the two important constraints in motion recognition: missing information and clutter outdoor motions. Two separate systems based on these constraints are also developed that shows the suitable adoption of the constraints. However, several people occupy a scene in practical cases. We have proposed a detection-tracking-recognition integrated action recognition system to deal with multiple people case. The system shows decent performance in outdoor scenarios. The experimental results empirically illustrate the suitability and compatibility of various factors of the motion recognition