Masayuki Kashima

A Non-invasive Facial Visual-Infrared Stereo Vision Based Measurement as an Alternative for Physiological Measurement

Our main aim is to propose a vision-based measurement as an alternative to physiological measurement for recognizing mental stress. The development of this emotion recognition system involved three stages: experimental setup for vision and physiological sensing, facial feature extraction in visual-thermal domain, mental stress stimulus experiment and data analysis and classification based on Support Vector Machine. In this research, 3 vision-based measurement and 2 physiological measurement were implemented in the system. Vision based measurement in facial vision domain consists of eyes blinking and in facial thermal domain consists 3 ROI’s temperature value and blood vessel volume at Supraorbital area. Two physiological measurement were done to measure the ground truth value which is heart rate and salivary amylase level. We also propose a new calibration chessboard attach with fever plaster to locate calibration point in stereo view. A new method of integration of two different sensors for detecting facial feature in both thermal and visual is also presented by applying nostril mask, which allows one to find facial feature namely nose area in thermal and visual domain. Extraction of thermal-visual feature images was done by using SIFT feature detector and extractor to verify the method of using nostril mask. Based on the experiment conducted, 88.6 % of correct matching was detected. In the eyes blinking experiment, almost 98 % match was detected successfully for without glasses and 89 % with glasses. Graph cut algorithm was applied to remove unwanted ROI. The recognition rate of 3 ROI’s was about 90 %–96 %. We also presented new method of automatic detection of blood vessel volume at Supraorbital monitored by LWIR camera. The recognition rate of correctly detected pixel was about 93 %. An experiment to measure mental stress by using the proposed system based on Support Vector Machine classification had been proposed and conducted and showed promising results.

New method for measuring the topology preservation of self-organizing feature maps

The topology preservation of self-organizing feature maps is an important property which is used in many applications. Various qualitative and quantitative approaches are known for measuring the degree of topology preservation. However, well-received measures for determining the topology preservation have not been presented yet. In this paper, we present a new method for measuring the degree of topology preservation based on the masked Delaunay triangulation. The topology preservation is completed when the masked Delaunay triangulation coincides with the output network shape. We demonstrate the usefulness of this measure for various examples of data manifolds. This method is also applied to measure the degree of topology preservation of the topology-representing network of T. Martinetz et al. (1994). In various simulations, this measure brought a reasonable degree of topology preservation.

A study on state recognition in wide area by aerial image analysis

In recent years, the technologies of computer vision and robotics have been developed rapidly and used in many fields, especially on wide-area surveillance. Previously, several studies on visual surveillance have been executed. However, problems of narrow field of view and poor tracking capability still exist. To solve these problems, we propose a new visual control method to achieve automatic human tracking for flying robot. The method consists in integrating multiple modules to detect the moving direction of human automatically and tracking the subject in real time by performing autonomous control of the flying robot. To achieve automatic human tracking, it is essential to detect the moving direction of the subject accurately. Therefore, an algorithm to integrate human detection, human tracking, contour extraction, and moving direction detection and prediction is proposed in our study. In addition, flying robot is controlled by the correct moving direction of human. Evaluation experiments are carried out in simple environment and cluttered environment. Experimental results utilizing flying robot have shown the effectiveness of the proposed method.