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The Hough transform is a feature extraction technique used in image analysis, computer vision and digital image processing. Usually it is used for detecting straight lines and curves. The purpose of the technique is to find imperfect instances of patterns within a certain class of shapes by a voting procedure. An improved Hough transform is proposed by using interval arithmetics in the accumulation...
This paper presents an unsupervised learning-based method for selection of feature points and object category classification to apply to a vision-based mobile robot. Our method has the following four capabilities. First, our method can localize target feature points using One Class-Support Vector Machines (OC-SVMs) without previous setting of boundary information. Second, our method can generate labels...
We constructed an image diagnosis support system for Alzheimer-type Dementia that extracts temporal lobe regions and an intracranial region as regions of interest (ROI) from a T2-weighted MR frontal image and uses the cerebral atrophy rates at the ROI. In this paper, we specifically discuss extraction of brain regions and diagnosis support information based on atrophy speeds of the ROI. The proposed...
It is an important issue that the relationship between personality and individual characteristic of an electroencephalogram (EEG) for using a personalized brain computer interface on daily basis. In this paper, we introduce a method for discussing the relationship between personality based on egogram scores and the results of the EEG pattern detection. The egogram based on psychological testing is...
This paper discusses the relationship the result classified the electroencephalogram (EEG) patterns while listening to music and the human's nature, which indicates the personal feature of a human, based on the egogram pattern. The EEG analysis calculates the power spectra of the frequency of the EEG signal, divides into the frequency bands based on theta, alpha, and beta rhythms, and evaluates whether...
This paper presents a method to generate individual Facial Expression Spatial Charts (FESC) using Self-Organizing Maps (SOM) and Fuzzy Adaptive Resonance Theory (ART) networks. We specifically examine the dynamic diversity of facial expressions in time-series facial images after conversion using Gabor wavelet filters. The proposed method consists of three steps: the first step is to extract topological...
In computer vision, background subtraction method is widely used to extract a changing region in a scene. However, it is difficult to simply apply this method to a scene with moving background object, because such object may be extracted as a changing region. Therefore, a method has been proposed to estimate both current background image and occluding object region simultaneously by using eigenspace-based...
In order to sufficiently represent and recognize human gestures, one needs, in the first place, to know at what frame rate a gesture should be sampled. To investigate the temporal-domain problems on gesture recognition, a framework is proposed that recognizes arbitrary gestures at multiple frame rate by running recognition processes in parallel. In our system, each recognition process runs on-line...
We propose a visual tracking system that downloads object models from the network. A visual ID-tag is attached onto each object, and the system identifies the object by recognizing the tag in the image. In order to realize robust recognition, we design a circular tag made of a retroreflector, and mount a lighting system that illuminates objects in sync with the camera. Observing the change of pixel...
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