Abstract We introduce and evaluate a novel camera pose estimation framework that uses the human head as calibration object. The proposed method facilitates extrinsic from 2D input images (NIR and/or RGB), while merely relying on detected head, without need for depth information. approach is applicable to single cameras or multi-camera networks. Our implementation fine-tuned deep learning-based ...

in this paper, we propose a novel method for fully automatic detection and tracking of human heads and faces in video sequences. the proposed algorithm consists of two modules: a face detection module and a face tracking module. the detection module, detects the face region and approximates it with an ellipse at the first frame using a modified version of adaboost cascaded classifier. the detec...

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...

Head pose estimation in low resolution is a challenge problem. Traditional pose estimation algorithms, which assume faces have been well aligned before pose estimation, would face much difficulty in this situation, since face alignment itself does not work well in this low resolution scenario. In this paper, we propose to estimate head pose using viewbased multi-view face detectors directly. Na...

This work addresses the problem of human head pose estimation from single view images. 3D rigid head pose is estimated combining Active Appearance Models (AAM) with Pose from Orthography and Scaling with ITerations (POSIT). AAM shape landmarks are tracked over time and used in POSIT for pose estimation. A statistical anthropometric 3D model is used as reference. Several experiences were perform...

Head pose estimation from a monocular camera or a simple image is a challenging topic. It is the process of inferring the orientation of a human head from digital imagery. Several processing steps are performed in order to transform a pixel-based representation of the head into a high-level concept of direction. The head pose is important in a lot of domains like human-computer interfaces, vide...

The capacity to create ”fake” videos has recently raised concerns about the reliability of multimedia content. Identifying between true and false information is a critical step toward resolving this problem. On issue, several algorithms utilizing deep learning facial landmarks have yielded intriguing results. Facial are traits that solely tied subject’s head posture. Based on observation, we st...

Many computer vision applications such as augmented reality require head pose estimation. As far as the implementation of head pose estimation on relatively resource limited mobile platforms is concerned, it is computationally challenging to meet the real-time constraints while maintaining reasonable head pose estimation accuracy. The discussed head pose estimation approach in this paper is an ...

Head pose estimation has been an integral problem in the study of face recognition systems and human-computer interfaces, as part of biometric applications. A fine estimate of the head pose angle is necessary and useful for several face analysis applications. To determine the head pose, face images with varying pose angles can be considered to be lying on a smooth low-dimensional manifold in hi...