scholarly journals Audiovisual speaker identity verification based on lip motion features

Author(s):  
Girija Chetty ◽  
Michael Wagner
2014 ◽  
Vol 1 (3) ◽  
pp. 8-17
Author(s):  
Shefali Sharma ◽  
◽  
Ashutosh Kumar Singh ◽  
Rajiv Saxena ◽  
◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3722
Author(s):  
Byeongkeun Kang ◽  
Yeejin Lee

Motion in videos refers to the pattern of the apparent movement of objects, surfaces, and edges over image sequences caused by the relative movement between a camera and a scene. Motion, as well as scene appearance, are essential features to estimate a driver’s visual attention allocation in computer vision. However, the fact that motion can be a crucial factor in a driver’s attention estimation has not been thoroughly studied in the literature, although driver’s attention prediction models focusing on scene appearance have been well studied. Therefore, in this work, we investigate the usefulness of motion information in estimating a driver’s visual attention. To analyze the effectiveness of motion information, we develop a deep neural network framework that provides attention locations and attention levels using optical flow maps, which represent the movements of contents in videos. We validate the performance of the proposed motion-based prediction model by comparing it to the performance of the current state-of-art prediction models using RGB frames. The experimental results for a real-world dataset confirm our hypothesis that motion plays a role in prediction accuracy improvement, and there is a margin for accuracy improvement by using motion features.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joël L. Lavanchy ◽  
Joel Zindel ◽  
Kadir Kirtac ◽  
Isabell Twick ◽  
Enes Hosgor ◽  
...  

AbstractSurgical skills are associated with clinical outcomes. To improve surgical skills and thereby reduce adverse outcomes, continuous surgical training and feedback is required. Currently, assessment of surgical skills is a manual and time-consuming process which is prone to subjective interpretation. This study aims to automate surgical skill assessment in laparoscopic cholecystectomy videos using machine learning algorithms. To address this, a three-stage machine learning method is proposed: first, a Convolutional Neural Network was trained to identify and localize surgical instruments. Second, motion features were extracted from the detected instrument localizations throughout time. Third, a linear regression model was trained based on the extracted motion features to predict surgical skills. This three-stage modeling approach achieved an accuracy of 87 ± 0.2% in distinguishing good versus poor surgical skill. While the technique cannot reliably quantify the degree of surgical skill yet it represents an important advance towards automation of surgical skill assessment.


Author(s):  
Donald Reising ◽  
Joseph Cancelleri ◽  
T. Daniel Loveless ◽  
Farah Kandah ◽  
Anthony Skjellum

JAMIA Open ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 479-488
Author(s):  
Bryan D Steitz ◽  
Joseph Isaac S Wong ◽  
Jared G Cobb ◽  
Brian Carlson ◽  
Gaye Smith ◽  
...  

Abstract Background and Objective Patient portal use has increased over the last two decades in response to consumer demand and government regulation. Despite growing adoption, few guidelines exist to direct successful implementation and governance. We describe the policies and procedures that have governed over a decade of continuous My Health at Vanderbilt (MHAV) patient portal use. Methods We examined MHAV usage data between May 2007 and November 2017. We classified patient portal activity into eight functional categories: Appointment, Billing, Document Access, Genetics, Health Result, Immunization, Medication, and Messaging. We describe our operating policies and measure portal uptake, patient account activity, and function use over time. Results By the end of the study period, there were 375 517 registered accounts. Policies made MHAV available to competent adults and adolescents 13 and over. Patients signed up for a limited access account online, which could be upgraded to a full-access account after identity verification. Patients could assign proxy accounts to family and caregivers, which permitted nonpatient access to select MHAV functions. Laboratory and radiology results were accessible via MHAV. Results were classified into three groups based on sensitivity, which govern the length of delay before results appeared in MHAV. Discussion and Conclusion Patient portals offer significant opportunity to engage patients in their healthcare. However, there remains a need to understand how policies can promote uptake and use. We anticipate that other institutions can apply concepts from our policies to support meaningful patient portal engagement.


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