https://cyberleninka.org/article/n/1450567.pdf

Beyond eye gaze: What else can eyetracking reveal about cognition and cognitive development?

Micro-expressions (MEs) are rapid, involuntary facial expressions which reveal emotions that people do not intend to show. Studying MEs is valuable as recognizing them has many important applications, particularly in forensic science and psychotherapy. However, analyzing spontaneous MEs is very challenging due to their short duration and low intensity. Automatic ME analysis includes two tasks: ME spotting and ME recognition. For ME spotting, previous studies have focused on posed rather than spontaneous videos. For ME recognition, the performance of previous studies is low. To address these challenges, we make the following contributions: (i) We propose the first method for spotting spontaneous MEs in long videos (by exploiting feature difference contrast). This method is training free and works on arbitrary unseen videos. (ii) We present an advanced ME recognition framework, which outperforms previous work by a large margin on two challenging spontaneous ME databases (SMIC and CASMEII). (iii) We propose the first automatic ME analysis system (MESR), which can spot and recognize MEs from spontaneous video data. Finally, we show our method outperforms humans in the ME recognition task by a large margin, and achieves comparable performance to humans at the very challenging task of spotting and then recognizing spontaneous MEs.

/pdf/towards-reading-hidden-emotions-a-comparative-study-of-3srvkfoye6.pdf

Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods

We investigate the appearance-based gaze estimation problem, with respect to its essential difficulty in reducing the number of required training samples, and other practical issues such as slight head motion, image resolution variation, and eye blinking. We cast the problem as mapping high-dimensional eye image features to low-dimensional gaze positions, and propose an adaptive linear regression (ALR) method as the key to our solution. The ALR method adaptively selects an optimal set of sparsest training samples for the gaze estimation via l(1)-optimization. In this sense, the number of required training samples is significantly reduced for high accuracy estimation. In addition, by adopting the basic ALR objective function, we integrate the gaze estimation, subpixel alignment and blink detection into a unified optimization framework. By solving these problems simultaneously, we successfully handle slight head motion, image resolution variation and eye blinking in appearance-based gaze estimation. We evaluated the proposed method by conducting experiments with multiple users and variant conditions to verify its effectiveness.

Adaptive Linear Regression for Appearance-Based Gaze Estimation.

A vision-based human--computer interface is presented in the paper. The interface detects voluntary eye-blinks and interprets them as control commands. The employed image processing methods include Haar-like features for automatic face detection, and template matching based eye tracking and eye-blink detection. Interface performance was tested by 49 users (of which 12 were with physical disabilities). Test results indicate interface usefulness in offering an alternative mean of communication with computers. The users entered English and Polish text (with average time of less than 12s per character) and were able to browse the Internet. The interface is based on a notebook equipped with a typical web camera and requires no extra light sources. The interface application is available on-line as open-source software.

/pdf/eye-blink-detection-system-for-human-computer-interaction-2rbb7tlayk.pdf

Eye-blink detection system for human---computer interaction

Eyes closeness detection from still images with multi-scale histograms of principal oriented gradients

In recent years there has been an increased interest in human-computer interaction systems allowing for more natural communication with machines. Such systems are especially important for the elderly and disabled persons. The paper presents a vision-based system for detection of long voluntary eye blinks and interpretation of blink patterns for communication between man and machine. The blink-controlled applications developed for this system have been described, i.e. the spelling program and the eye-controlled Web browser.

Vision-based eye blink monitoring system for human-computer interfacing

In recent years there has been an increased interest in Human-Computer Interaction Systems allowing for more natural communication with machines Such systems are especially important for elderly and disabled persons The paper presents a vision-based system for detection of long voluntary eye blinks and interpretation of blink patterns for communication between man and machine The blink-controlled applications developed for this system have been described, ie the spelling program and the eye-controlled web browser

Eye-Blink Controlled Human-Computer Interface for the Disabled

The development of Massive Open Online Courses (MOOCs) has provided unique learning opportunities for many people. In the meantime, the lack of accessibility in some MOOCs has also created barriers for diverse learners. In this paper, we present the preliminary results from a study on the accessibility a selected set of MOOCs on the Coursera platform for blind learners who use screen readers and Braille to interact with computers and mobile devices.

/pdf/the-accessibility-of-moocs-for-blind-learners-3f9lwx9qi3.pdf

The Accessibility of MOOCs for Blind Learners

Non-contact methods of human heart rate (HR) facilitate medical assessment of this most important vital sign and increase patient comfort. Videoplethysmograpy (VPG) can be applied not only in healthcare units but also at homes and remote locations. In this paper the efficiency of an algorithm for pulse rate detection based on face image is analyzed. The correspondence between patient ethnicity and various color components used for HR estimation is examined. The results suggest that analysis of color components related to red provide better performance in case of darker skin tone, while green-related components are more accurate for persons of Caucasian origin.

Aleksandra Królak

Papers

Eye-blink detection system for human---computer interaction

Vision-based eye blink monitoring system for human-computer interfacing

Eye-Blink Controlled Human-Computer Interface for the Disabled

The Accessibility of MOOCs for Blind Learners

Influence of Skin Tone on Efficiency of Vision-Based Heart Rate Estimation