We present a template-based approach to detecting human silhouettes in a specific walking pose. Our templates consist of short sequences of 2D silhouettes obtained from motion capture data. This lets us incorporate motion information into them and helps distinguish actual people who move in a predictable way from static objects whose outlines roughly resemble those of humans. Moreover, during t...

Human pose estimation is a vivid topic in current literature due to its wide-spread applications such as motion-capture, telepresence or object manipulation in virtual environments. The process of human pose estimation is concerned with finding the pose parameters of a human body model that best fit to the observations in one or more input images. There exists a variety of algorithms that solve...

We present a human body motion tracking system for an interactive virtual simulation training environment. This system captures images using IR illumination and near-IR cameras to overcome limitations of a dimly lit environment. Features, such as silhouettes and medial axis of blobs are extracted from the images which lack much internal texture. We use a combination of a 2D ICP and particle fil...

We present a framework to estimate 3D body configuration and view point from a single uncalibrated camera. We model shape deformations corresponding to both view point and body configuration changes through the motion. Such observed shapes present a product space (different configurations × different views) and therefore lie on a two dimensional manifold in the visual input space. The approach ...

To investigate the task of multidimensional continuous inference from video sequences on a concrete example application, we focus on the problem of articulated 3D human tracking from monocular video. This is an interesting topic because of its relevance for biological vision systems, as well as its many applications in various domains. Estimating body pose and motion of humans is a challenging ...

Particle filtering is a popular method used in systems for tracking human body pose in video. One key difficulty in using particle filtering is caused by the curse of dimensionality: generally a very large number of particles is required to adequately approximate the underlying pose distribution in a high-dimensional state space. Although the number of degrees of freedom in the human body is qu...

Human-Computer Interaction (HCI) is the study of interaction between people (users) and computers. The recent advances in computing technology push the interest in human-computer interaction in other ways than the traditional keyboard, mouse or keypad devices. The work presented in this thesis uses computer vision to enhance the HCI, by introducing novel real-time and marker-less gesture and bo...

H UMAN Body Pose Estimation (HBPE) is the process of identifying how a human body and/or its individual limbs are configured in a given scene [9]. The importance of such task has been identified by the computer vision community which has dedicated a large amount of effort towards finding an effective solution. A wide variety of techniques have been proposed in an attempt of finding the one whic...

This paper presents a new annealing method for particle filtering in the context of body pose estimation. The feature-based annealing is inferred from the weighting functions obtained with common image features used for the likelihood approximation. We introduce a complementary weighting function based on the foreground extraction and we balance the different measures through the annealing laye...

This paper presents a method of interpolating between two or more general displacements (rotation and translation). The resulting interpolated path is smooth and possesses a number of desirable properties. It differs from existing algorithms which require factorising the pose into separate rotation and translation components and is derived from an intuitively appealing framework – i.e. a natura...