Despite active research and significant progress in the last 30 years, eye detection and tracking remains challenging due to the individuality of eyes, occlusion, variability in scale, location, and light conditions. Data on eye location and details of eye movements have numerous applications and are essential in face detection, biometric identification, and particular human-computer interaction tasks. This paper reviews current progress and state of the art in video-based eye detection and tracking in order to identify promising techniques as well as issues to be further addressed. We present a detailed review of recent eye models and techniques for eye detection and tracking. We also survey methods for gaze estimation and compare them based on their geometric properties and reported accuracies. This review shows that, despite their apparent simplicity, the development of a general eye detection technique involves addressing many challenges, requires further theoretical developments, and is consequently of interest to many other domains problems in computer vision and beyond.

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In the Eye of the Beholder: A Survey of Models for Eyes and Gaze

The capacity to estimate the head pose of another person is a common human ability that presents a unique challenge for computer vision systems. Compared to face detection and recognition, which have been the primary foci of face-related vision research, identity-invariant head pose estimation has fewer rigorously evaluated systems or generic solutions. In this paper, we discuss the inherent difficulties in head pose estimation and present an organized survey describing the evolution of the field. Our discussion focuses on the advantages and disadvantages of each approach and spans 90 of the most innovative and characteristic papers that have been published on this topic. We compare these systems by focusing on their ability to estimate coarse and fine head pose, highlighting approaches that are well suited for unconstrained environments.

Head Pose Estimation in Computer Vision: A Survey

Surveys the developments of the last 20 years in the area of vision for mobile robot navigation. Two major components of the paper deal with indoor navigation and outdoor navigation. For each component, we have further subdivided our treatment of the subject on the basis of structured and unstructured environments. For indoor robots in structured environments, we have dealt separately with the cases of geometrical and topological models of space. For unstructured environments, we have discussed the cases of navigation using optical flows, using methods from the appearance-based paradigm, and by recognition of specific objects in the environment.

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Vision for mobile robot navigation: a survey

หนงสอ Behavioral Game Theory: Experiments in Strategic Interaction เขยนโดย Colin F. Camerer มวตถประสงคเพอนำเสนอหลกฐานเชงประจกษจากผลการวจยจำนวนมากมายทยนยนอทธพลของปจจยทางจตวทยาทมผลตอการตดสนใจตามทฤษฎเกม หนงสอ เลมนไดนำเสนอแนวคดทฤษฎทเพมความสามารถในการอธบายพฤตกรรมการตดสนใจตามทฤษฎเกม (Game theory) ซง von Neumann; & Morgenstern ไดเสนอไวในป ค.ศ. 1944 โดยชใหเหนวา ปจจยทางจตวทยามอทธพลทำใหการตดสนใจทเกดขนจรงคลาดเคลอนจากการคาดการณของทฤษฎเกม

Behavioral Game Theory: Experiments in Strategic Interaction

https://www.cse.unr.edu/~mircea/Publications/mn_cviu07.pdf

Vision-based hand pose estimation: A review

To build smart human interfaces, it is necessary for a system to know a user's intention and point of attention. Since the motion of a person's head pose and gaze direction are deeply related with his/her intention and attention, detection of such information can be utilized to build natural and intuitive interfaces. We describe our real-time stereo face tracking and gaze detection system to measure head pose and gaze direction simultaneously. The key aspect of our system is the use of real-time stereo vision together with a simple algorithm which is suitable for real-time processing. Since the 3D coordinates of the features on a face can be directly measured in our system, we can significantly simplify the algorithm for 3D model fitting to obtain the full 3D pose of the head compared with conventional systems that use monocular camera. Consequently we achieved a non-contact, passive, real-time, robust, accurate and compact measurement system for head pose and gaze direction.

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An algorithm for real-time stereo vision implementation of head pose and gaze direction measurement

Previous work in vision-based mobile robotics have lacked models of the route which can be utilized for (1) localization, (2) steering angle determination, and (3) obstacle detection, simultaneously. In this paper, the authors propose a new visual representation of the route, the "view-sequenced route representation (VSRR)." The VSRR is a non-metrical model of the route, which contains a sequence of front view images along a route memorized in the recording run. In the autonomous run, the three types of recognition described above are achieved in real-time by matching between the current view image and the memorized view sequence using a correlation technique. the authors also developed an easy procedure for acquiring VSRRs, and a quick control procedure using VSRRs. VSRRs are especially useful for representing routes in corridors. Results of autonomous navigation using a two-wheeled robot in a real corridor are also presented.

Visual navigation using view-sequenced route representation

Computer systems which analyse human face/head motion have attracted significant attention recently as there are a number of interesting and useful applications. Not least among these is the goal of tracking the head in real time. A useful extension of this problem is to estimate the subject's gaze point in addition to his/her head pose. This paper describes a real-time stereo vision system which determines the head pose and gaze direction of a human subject. Its accuracy makes it useful for a number of applications including human/computer interaction, consumer research and ergonomic assessment.

Real-time stereo tracking for head pose and gaze estimation

This paper proposes a novel method for a hand-pose estimation that can be used for vision-based human interfaces. The aim of this method is to estimate all joint angles. In this method, the hand regions are extracted from multiple images obtained by a multiviewpoint camera system. By integrating these multiviewpoint silhouette images, a hand pose is reconstructed as a "voxel model." Then, all joint angles are estimated using a three-dimensional model fitting between the hand model and the voxel model. The following two experiments were performed: (1) an estimation of joint angles by the silhouette images from the hand-pose simulator and (2) hand-pose estimation using real hand images. The experimental results indicate the feasibility of the proposed algorithm for vision-based interfaces, although the algorithm requires faster implementation for real-time processing.

A hand-pose estimation for vision-based human interfaces

Recently, view-based or appearance-based approaches have been attracting the interests of computer vision research. Based on a similar idea, we have proposed a view-based navigation method using a model of the route called the "view sequence." It contains a sequence of frontal views along a route memorized in the teaching run, and the recognition of the environment is realized based on the matching of the current view and memorized view sequence. In this paper, we discuss the required characteristics of the view for the view sequence, and evaluate our former method of generating views. Then we confirm that the stereo disparity satisfies the requirement of the view sequence through an experiment, and the disparity view sequence is applied for outdoor navigation. The experimental results indicate such views other than normal camera images can be utilized for our view-based navigation method.

Yoshio Matsumoto

Papers

An algorithm for real-time stereo vision implementation of head pose and gaze direction measurement

Visual navigation using view-sequenced route representation

Real-time stereo tracking for head pose and gaze estimation

A hand-pose estimation for vision-based human interfaces

View-based approach to robot navigation