The task of 2-D articulated human pose estimation in natural images is extremely challenging due to the high level of variation in human appearance. These variations arise from di...
In this paper we propose a novel appearance descriptor for 3D human pose estimation from monocular images using a learning-based technique. Our image-descriptor is based on the int...
This paper presents a learning-based method for combining the shape and appearance feature types for 3D human pose estimation from single-view images. Our method is based on clust...
We investigate the task of 2D articulated human pose estimation in unconstrained still images. This is extremely challenging because of variation in pose, anatomy, clothing, and i...
Pose estimation has been considered to be an important component in many pattern recognition and computer vision systems. In this paper, we introduce a pose estimation method base...
This paper explores the possibility of a linear model as a solution to the problem of appearance-based pose estimation. The parametric eigenspace method (or its extensions that ar...
The detection and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes, and the high dimensio...
Leonid Sigal, Michael Isard, Benjamin H. Sigelman,...
An approach to multi-view face detection based on head pose estimation is presented in this paper. Support Vector Regression is employed to solve the problem of pose estimation. T...
We describe a novel method for real-time, simultaneous multi-view face detection and facial pose estimation. The method employs a convolutional network to map face images to point...
We present a generic and robust method for model-based global 3D head pose estimation in monocular and non-calibrated video sequences. The proposed method relies on a 3D/2D matchi...