Naoki Mukawa

FreeGaze: a gaze tracking system for everyday gaze interaction

In this paper we introduce a novel gaze tracking system called FreeGaze, which is designed for the use of everyday gaze interaction. Among various possible applications of gaze tracking system, Human-Computer Interaction (HCI) is one of the most promising elds. However, existing systems require complicated and burden-some calibration and are not robust to the measurement variations. To solve these problems, we introduce a geometric eyeball model and sophisticated image processing. Unlike existing systems, our system needs only two points for each individual calibration. When the personalization nishes, our system needs no more calibration before each measurement session. Evaluation tests show that the system is accurate and applicable to everyday use for the applications.

A free-head, simple calibration, gaze tracking system that enables gaze-based interaction

Human eye gaze is a strong candidate to create a new application area based on human-computer interaction. To implement a really practical gaze-based interaction system, gaze detection must be realized without placing any restriction on the users behavior or comfort. This paper describes a gaze tracking system that offers freehead, simple personal calibration. It does not require the user wear anything on her head, and she can move her head freely. Personal calibration takes only a very short time; the user is asked to look at two markers on the screen. An experiment shows that the accuracy of the implemented system is about 1.0 degrees (view angle).

Just blink your eyes: a head-free gaze tracking system

We propose a head-free, easy-setup gaze tracking system designed for a gaze-based Human-Computer Interaction. Our system enables the user to interact with the computer soon after catching the users eye blinks. The user can move his/her head freely since the system keeps tracking the users eye. In addition, our system only needs a 10 second calibration procedure at the very first time of use. An eye tracking method based on our unique eye blink detection and a sophisticated gaze estimation method using the geometrical eyeball model realize these advantages.

Multiview occlusion analysis for tracking densely populated objects based on 2-D visual angles

A novel framework of multiview occlusion analysis is presented for tracking densely populated objects moving on two-dimensional plane. This paper explicitly models the spatial structure of the occlusion process between objects and its uncertainty, based on 2D silhouette-based visual angles from fixed viewpoints. The occlusion structure is defined as tangency combination between the objects and the edges of the visual angles, based on geometric constraints inherent in the visual angles. The problem is then formulated as recursive Bayesian estimation consisting of hypothesis generation/testing of the occlusion structure and the estimation of posterior probability distribution for the object states including position and posture, on each hypothesis of the occlusion structure. For implementing the proposed framework, we develop a novel type of particle filter that supports multiple state distributions. Experiments using synthetic and real data show the robustness of the framework even in the face of severe occlusions.

Kernel mutual subspace method for robust facial image recognition

A multiple observation-based scheme (MObS) is described for robust facial recognition, and a novel object recognition method called kernel mutual subspace method (KMS) is proposed. The mutual sub-space method (MSM) proposed by (Maeda, et al., 1999) is a powerful method for recognizing facial images. However, its recognition accuracy is degraded when the data distribution has a nonlinear structure. To overcome this shortcoming we apply kernel principal component analysis (kPCP) to MSM. This paper describes theoretical aspects of the proposed method and presents the results of facial image recognition experiments.

Detecting changes of buildings from aerial images using shadow and shading model

We propose a method for detecting changes of buildings by comparing aerial images which are taken at different times. In the proposed method, we consider the shadow and shading model. The model is derived from a relation between incident light of the Sun and 3D shapes of buildings which intercept the incident light. The advantage of the proposed method is that we only compare 2D aerial images based on the model without estimating 3D shapes of buildings. When we compare the aerial images, we have the problem that changes of shadows and buildings are observed simultaneously in the images. To solve this problem, we propose criteria for distinguishing the changes of shadows and buildings. Our experiments have shown that the proposed method can distinguish the changes of shadows and buildings in real aerial images.

Estimation of homogeneous regions for segmentation of textured images

In this paper a novel method for the unsupervised segmentation of textured images is presented. Textures are modeled as spatial interactions between pixels. Thus, a certain window size is required to extract texture features and to estimate texture boundaries by using the features. As long as the size of the window is fixed over the whole of an image, we cannot accurately estimates texture regions that have similar properties. In this paper the problem of selection of an appropriate size for window used to estimate homogeneous texture regions is investigated via hypothesis and testing. Experiments on segmentation of textures in synthetic and natural images show the effectiveness of the method.

What is connected by mutual gaze?: user's behavior in video-mediated communication

Video-mediated communication systems such as teleconferencing and videophone have become popular. As with face-to-face communication, non-verbal cues such as gaze, facial expression, head orientation and gestures in visual systems play an important role. Existing systems, however, do not support mutual gaze because the lay-out of the camera and monitor is restricted. Thus, conversations using visual systems differ from those in face-to-face communication. This paper clarifies the problems of the video-mediated system, specifically for comparing the system with communication using eye-contact and with communication using no-eye-contact. This study focuses on the protocol of opening communication, e.g. establishment of a visual-audio link, person identification and confirmation of the acceptance of conversation. We conducted experiments using the two systems. Analysis of recorded video sequences revealed that the system using communication with eye-contact induced behavior similar to the system using face-to-face communication.

An object-based image retrieval system using an inhomogeneous diffusion model

This paper proposes a novel object-based method to similar image retrieval by representing an image by its salient object regions as well as associated color texture and shape features. The major obstacle in developing such methods is the difficulty of accurately segmenting the image into prominent regions. To overcome this difficulty we applied an inhomogeneous diffusion model to both color and texture features to quasi-accurately detect salient regions in the image. Characteristic color texture and shape features of these regions are obtained on the basis of diffusion results. These features are invariant to rotation. Scale invariance was also achieved for the color and shape features. A suitable user interface was developed to facilitate object-based searches. Enabling the user to specify the objects he/she is looking for ensures a higher level of performance and flexibility. Experiments conducted on a large number of images taken from Corel and Kodak photo-CD data show that the method performs well for a large variety of natural images.

An utterance attitude model in human-agent communication: from good turn-taking to better human-agent understanding

In this study, we discuss a novel expression and comprehension model of the utterance attitude of speaking/hearing during conversations. Humans who participate in conversation display these implicit and explicit attitudes, and use them to understand the other participants in advance of turn-taking. We design abstract animated agents that mimic human turntaking in conversations to confirm the validity of our model. The subjective evaluation tests show that the expressions of the agents are understandable. The model may facilitate turn-taking in human-agent interaction.