Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
OBBTree: a hierarchical structure for rapid interference detection
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
3D point-of-regard, position and head orientation from a portable monocular video-based eye tracker
Proceedings of the 2008 symposium on Eye tracking research & applications
EPnP: An Accurate O(n) Solution to the PnP Problem
International Journal of Computer Vision
The Pascal Visual Object Classes (VOC) Challenge
International Journal of Computer Vision
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera
Proceedings of the 24th annual ACM symposium on User interface software and technology
Attentive object detection using an information theoretic saliency measure
WAPCV'04 Proceedings of the Second international conference on Attention and Performance in Computational Vision
A general method for the point of regard estimation in 3D space
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
3D attention: measurement of visual saliency using eye tracking glasses
CHI '13 Extended Abstracts on Human Factors in Computing Systems
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The study of human attention in the frame of interaction studies has been relevant for usability engineering and ergonomics for decades. Today, with the advent of wearable eye-tracking and Google glasses, monitoring of human attention will soon become ubiquitous. This work describes a multi-component vision system that enables pervasive mapping of human attention. The key contribution is that our methodology enables full 3D recovery of the gaze pointer, human view frustum and associated human centered measurements directly into an automatically computed 3D model. We apply RGB-D SLAM and descriptor matching methodologies for the 3D modeling, localization and fully automated annotation of ROIs (regions of interest) within the acquired 3D model. This methodology brings new potential into automated processing of human factors, opening new avenues for attention studies.