Pose problem presents a challenge to face recognition methods because the shapes and features of the human face with large pose angle often appear quite different from the template. One approach to overcome this problem involves the estimation of the angle to which the face is rotated and then matches it to templates with the same pose. Another approach involves aligning the key facial features...

We present the 2017 Hands in the Million Challenge, a public competition designed for the evaluation of the task of 3D hand pose estimation. The goal of this challenge is to assess how far is the state of the art in terms of solving the problem of 3D hand pose estimation as well as detect major failure and strength modes of both systems and evaluation metrics that can help to identify future re...

We present an automatic method for locating facial features and estimating head pose in 2D images and video using a 3D shape model and local view-based texture patches. After automatic initialization, the 3D pose and shape are refined iteratively to optimize the match between the appearance predicted by the model, and the image. The local texture patches are generated using the current 3D pose ...

This demo shows a robust model-based tracker using stereovision. The combined use of a 3D model with stereoscopic analysis allows accurate pose estimation in the presence of partial occlusions by non rigid objects like the hands of the user. Furthermore, using a second camera improves the stability of tracking and also simplifies the algorithm.

This paper addresses the problem of estimating head pose over a wide range of angles from low-resolution images. Faces are detected using chrominance-based features. Grey-level normalized face imagettes serve as input for linear auto-associative memory. One memory is computed for each pose using a Widrow-Hoff learning rule. Head pose is classified with a winner-takes-all process. We compare res...

Circular features have been commonly used in numerous computer vision application areas for 3-D pose estimation. However, the estimation of such a feature’s pose from 2-D image coordinates results in an orientation-duality problem. Namely, although the 3-D position of the circle’s center can be uniquely identified, the solution process yields two different feasible orientations, of which only o...

Tree-structured models have been widely used for human pose estimation, in either 2D or 3D. While such models allow efficient learning and inference, they fail to capture additional dependencies between body parts, other than kinematic constraints. In this paper, we consider the use of multiple tree models, rather than a single tree model for human pose estimation. Our model can alleviate the l...

Head pose estimation is recently a more and more popular area of research. For the last three decades new approaches have constantly been developed, and steadily better accuracy was achieved. Unsurprisingly, a very broad range of methods was explored statistical, geometrical and tracking-based to name a few. This paper presents a brief summary of the evolution of head pose estimation and a glim...

In this paper, a new method is presented to estimate the 3D pose of facial image based on statistical Gaussian error models. The basic idea is that the pose angle can be computed by the orthogonal projection computation if the specific 3D shape vector of the given person is known. In our algorithm, Gaussian probability density function is used to model the distributions of the 3D shape vector a...