In this work, we address the problem of human pose estimation in still images by proposing a holistic model for learning the appearance of the human body from image patches. These patches, which are randomly chosen, are used for extracting features and training a regression forest. During training, a mapping between image features and human poses, defined by joint offsets, is learned; while dur...

This paper describes a new method for matching line segments between two images in order to compute the relative camera pose. This approach improves the camera pose for images lacking stable point features but where straight line segments are available. The line matching algorithm is divided into two stages: At first, scale-invariant feature points along the lines are matched incorporating a on...

Analysis of driver’s head behavior is an integral part of driver monitoring system. In particular, head pose and dynamics are strong indicators of driver’s focus of attention. In this paper, we present a distributed camera framework for head pose estimation with emphasis on the ability to operate reliably and continuously. To evaluate the proposed framework, we collected a novel head pose datas...

This paper explores the capabilities of convolutional neural networks to deal with a task that is easily manageable for humans: perceiving 3D pose of a human body from varying angles. However, in our approach, we are restricted to using a monocular vision system. For this purpose, we apply a convolutional neural network approach on RGB videos and extend it to three dimensional convolutions. Thi...

Estimation of camera pose from image to space feature correspondence is a basic problem in image analysis and understanding. This paper presents a new method for the estimation of camera pose from 2D to 3D corner correspondence. Two cases are considered: the orthogonal corner and the general corner. The contribution of the work is in two folds: one is that the camera pose parameters, i.e., the ...

We propose a method for making globally consistent pose estimates using vision. Lu and Milios described an approach where the links between poses were estimated using range scanner data. When using point correspondences the length of the links cannot be estimated and the approach of Lu and Milios has to be modified. First we use the nonlinear orientation part of the pose differences to obtain a...

We study the problem of estimating the position and orientation of a calibrated camera from an image of a known scene. A common problem in camera pose estimation is the existence of false correspondences between image features and modeled 3D points. Existing techniques such as ransac to handle outliers have no guarantee of optimality. In contrast, we work with a natural extension of the L∞ norm...

Model-based pose estimation algorithms aim at recovering human motion from one or more camera views and a 3D model representation of the human body. The model pose is usually parameterized with a kinematic chain and thereby the pose is represented by a vector of joint angles. The majority of algorithms are based on minimizing an error function that measures how well the 3D model fits the image....

Predication of a pedestrian’s 3D pose using movie sequences is not straightforward because of the human body’s articulation and the complexity of biped locomotion. In this paper we show how temporal coherence can be employed to help the reconstruction of gait pose using corresponding silhouette moments of a video sequence from a monocular view. Virtual avatars were used to train the model for i...

Ongoing work towards appearance-based 3D hand pose estimation from a single image is presented. A large database of synthetic hand views is generated using a 3D hand model and computer graphics. The views display different hand shapes as seen from arbitrary viewpoints. Each synthetic view is automatically labeled with parameters describing its hand shape and viewing parameters. Given an input i...