Image based recognition of gaze direction using adaptive methods

Varchmin, Axel Christian; Rae, Robert; Ritter, Helge

doi:10.1007/bfb0053004

Cited by 14 publications

(6 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A number of techniques are known for estimating gaze direction of faces in images [13]. Such a process would recognizes that the woman in Figure 7 is facing to the right and that the man in Figure 7 is facing to the left.…”

Section: Gaze Direction Detectionmentioning

confidence: 99%

Content aware video presentation on high-resolution displays

Forlines

2008

Proceedings of the Working Conference on Advanced Visual Interfaces

View full text Add to dashboard Cite

We describe a prototype video presentation system that presents a video in a manner consistent with the video's content. Our prototype takes advantage of the physically large display and pixel space that current high-definition displays and multi-monitor systems offer by rendering the frames of the video into various regions of the display surface. The structure of the video informs the animation, size, and the position of these regions. Additionally, previously displayed frames are often allowed to remain on-screen and are filtered over time. Our prototype presents a video in a manner that not only preserves the continuity of the story, but also supports the structure of the video; thus, the content of the video is reflected in its presentation, arguably enhancing the viewing experience. AVI 2008This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Content Aware Video Presentation on High-Resolution Displays Clifton Forlines Mitsubishi Electric Research LabsCambridge, MA 02139 USA forlines@merl.com ABSTRACTWe describe a prototype video presentation system that presents a video in a manner consistent with the video's content. Our prototype takes advantage of the physically large display and pixel space that current high-definition displays and multi-monitor systems offer by rendering the frames of the video into various regions of the display surface. The structure of the video informs the animation, size, and the position of these regions. Additionally, previously displayed frames are often allowed to remain on-screen and are filtered over time. Our prototype presents a video in a manner that not only preserves the continuity of the story, but also supports the structure of the video; thus, the content of the video is reflected in its presentation, arguably enhancing the viewing experience.

show abstract

Section: Gaze Direction Detectionmentioning

confidence: 99%

Content aware video presentation on high-resolution displays

Forlines

2008

Proceedings of the Working Conference on Advanced Visual Interfaces

View full text Add to dashboard Cite

show abstract

“…There exist many different approaches for pose estimation, including pose estimation with color blobs [3; 17], pose estimation applying a geometrical approach [7], stereo information [25] or neural networks [1], to cite just a few. While in some approaches, such as in [17], only an approximate pose is estimated, other approaches have the goal to be very precise so that they could even be used as a basis for gaze detection such as in [23]. The precision of the geometrical approach [7] was extensively tested and verified in [15].…”

Section: Pose Estimation With Gwnmentioning

confidence: 99%

Efficient Head Pose Estimation with Gabor Wavelet Networks

Krüger

Sommer²

2000

Procedings of the British Machine Vision Conference 2000

View full text Add to dashboard Cite

In this article we want to introduce first the Gabor wavelet network as a model based approach for an effective and efficient object representation. The Gabor wavelet network has several advantages such as invariance to some degree with respect to translation, rotation and dilation. Furthermore, the use of Gabor filters ensured that geometrical and textural object features are encoded. The feasibility of the Gabor filters as a model for local object features ensures a considerable data reduction while at the same time allowing any desired precision of the object representation ranging from a sparse to a photo-realistic representation. In the second part of the paper we will present an approach for the estimation of a head pose that is based on the Gabor wavelet networks. 1. By their very nature, Gabor wavelet networks are invariant to some degree to affine deformations and homogeneous illumination changes,

show abstract

“…Our approach is based on an initial registration of facial landmarks of people when they are talking. This is common for traditional facial vision tasks like face [3], emotion [4], [5] or gaze [6] recognition. Whereas the recognition targets for these tasks are typically related to visual facial properties, we instead specifically attempt to recognize speech properties.…”

Section: Introductionmentioning

confidence: 99%

Detecting Speech Impairments from Temporal Visual Facial Features of Aphasia Patients

Einfalt

Lienhart

Lee

et al. 2019

2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)

View full text Add to dashboard Cite

We present an approach to detect speech impairments from video of people with aphasia, a neurological condition that affects the ability to comprehend and produce speech. To counter inherent privacy issues, we propose a crossmedia approach using only visual facial features to detect speech properties without listening to the audio content of speech. Our method uses facial landmark detections to measure facial motion over time. We show how to detect speech and pause instances based on temporal mouth shape analysis and identify repeating mouth patterns using a dynamic warping mechanism. We relate our developed features for pause frequency, mouth pattern repetitions, and pattern variety to actual symptoms of people with aphasia in the AphasiaBank dataset. Our evaluation shows that our developed features are able to reliably differentiate dysfluent speech production of people with aphasia from those without aphasia with an accuracy of 0.86. A combination of these handcrafted features and further statistical measures on talking and repetition improves classification performance to an accuracy of 0.88.

show abstract

Image based recognition of gaze direction using adaptive methods

Cited by 14 publications

References 7 publications

Content aware video presentation on high-resolution displays

Content aware video presentation on high-resolution displays

Efficient Head Pose Estimation with Gabor Wavelet Networks

Detecting Speech Impairments from Temporal Visual Facial Features of Aphasia Patients

Contact Info

Product

Resources

About