In this work we consider the challenging task of articulated human pose estimation in monocular images. Most of current methods in this area [4, 8, 16, 14] are based on the pictorial structures model (PS) and are composed of unary terms modelling body part appearance and pairwise terms between adjacent body parts and/or joints capturing their preferred spatial arrangement. In this work we advan...

In this paper, we introduce a framework for shape outlier, like carrying object, detection in different people from different views using pose preserving dynamic shape models. We model dynamic human shape deformations in different people using kinematics manifold embedding and decomposition of nonlinear mapping using kernel map and multilinear analysis. The generative model supports pose-preser...

We investigate how video-based recognition of rat social behavior is affected by two common tracking errors – animal misidentification and inaccurate localization of body parts. Our analyses show that correct identification is required to accurately recognize interactions. Precise localization of body points is beneficial for recognizing interactions that are described by a distinct pose. Inclu...

Accurate motion capture plays an important role in sports analysis, the medical field and virtual reality. Current methods for motion capture often suffer from occlusions, which limits the accuracy of their pose estimation. In this paper, we propose a complete system to measure the pose parameters of the human body accurately. Different from previous monocular depth camera systems, we leverage ...

We address the problem of estimating human body pose from a single image with cluttered background. We train multiple local linear regressors for estimating the 3D pose from a feature vector of gradient orientation histograms. Each linear regressor is capable of selecting relevant components of the feature vector depending on pose by training it on a pose cluster which is a subset of the traini...

This paper introduces a new image-based rendering approach for articulated objects with complex pose-dependent appearance, such as clothes. Our approach combines body-pose-dependent appearance and geometry to synthesize images of new poses from a database of examples. A geometric model allows animation and view interpolation, while small details as well as complex shading and reflection propert...

To solve the problem of relative camera pose estimation, a method using optimization with respect to the manifold is proposed. Firstly from maximum-a-posteriori (MAP) model to nonlinear least squares (NLS) model, the general state estimation model using optimization is derived. Then the camera pose estimation model is applied to the general state estimation model, while the parameterization of ...

In this paper, we address the problem of 3D human body pose estimation from depth images acquired by a stereo camera. Compared to the Kinect sensor, stereo cameras work outdoors having a much higher operational range, but produce noisier data. In order to deal with such data, we propose a framework for 3D human pose estimation that relies on random forests. The first contribution is a novel gri...

When learning to recognize a novel body shape, e.g., a panda bear, we are not misled by changes in its pose. A "jumping panda bear" is readily recognized, despite having no prior visual experience with the conjunction of these concepts. Likewise, a novel pose can be estimated in an invariant way, with respect to the actor’s body shape. These body and pose recognition tasks require invariance to...