Visual Search Target Inference in Natural Interaction Settings with Machine Learning-Reference-Cited by-同舟云学术

Visual Search Target Inference in Natural Interaction Settings with Machine Learning

Published:2020-05-05 Issue: Volume: Page:
ISSN:
Container-title:ACM Symposium on Eye Tracking Research and Applications
language:
Short-container-title:

Author:

Barz Michael¹,Stauden Sven²,Sonntag Daniel³

Affiliation:

1. German Research Center for Artificial Intelligence, Germany

2. Saarland University

3. German Research Center for Artificial Intelligence

Funder

EIT Digital

Bundesministerium für Bildung und Forschung

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3379155.3391314

Reference38 articles.

1. Gaze Augmentation in Egocentric Video Improves Awareness of Intention

2. Vijay Badrinarayanan Alex Kendall and Roberto Cipolla. 2015. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation. CoRR abs/1511.00561(2015) 14. arxiv:1511.00561http://arxiv.org/abs/1511.00561 Vijay Badrinarayanan Alex Kendall and Roberto Cipolla. 2015. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation. CoRR abs/1511.00561(2015) 14. arxiv:1511.00561http://arxiv.org/abs/1511.00561

3. Prediction of gaze estimation error for error-aware gaze-based interfaces

4. Error-aware gaze-based interfaces for robust mobile gaze interaction

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