A Hilbert warping method for camera-based finger-writing recognition, in:

Abstract We propose a time-warping algorithm for recognizing finger actions by a camera. In the proposed method, an input image sequence is aligned to the reference sequences by phase-synchronization of the analytic signals, and then classified by comparing the cumulative distances. A major benefit of this method is that overfitting to sequences of incorrect categories is restricted. The proposed method exhibited high recognition accuracy in finger-writing character recognition

Resting-state functional connectivity predicts recovery from visually induced motion sickness

映像酔いからの回復時に脳結合の増加を発見 --酔いの回復を促す技術開発の足がかりに--. 京都大学プレスリリース. 2021-01-14.Movies depicting certain types of motion often provoke uncomfortable symptoms similar to motion sickness, termed visually induced motion sickness (VIMS). VIMS generally evolves slowly during the viewing of a motion stimulus and, when the stimulus is removed, the recovery proceeds over time. Recent human neuroimaging studies have provided new insights into the neural bases of the evolution of VIMS. In contrast, no study has investigated the neural correlates of the recovery from VIMS. Study of the recovery process is critical for the development of a way to promote recovery and could provide further clues for understanding the mechanisms of VIMS. We thus investigated brain activity during the recovery from VIMS with functional connectivity magnetic resonance imaging. We found enhanced recovery-related functional connectivity patterns involving brain areas such as the insular, cingulate and visual cortical regions, which have been suggested to play important roles in the emergence of VIMS. These regions also constituted large interactive networks. Furthermore, the increase in functional connectivity was correlated with the subjective awareness of recovery for the following five pairs of brain regions: insula–superior temporal gyrus, claustrum–left and right inferior parietal lobules, claustrum–superior temporal gyrus and superior frontal gyrus–lentiform nucleus. Considering the previous findings on the functions of these regions and the present results, it is suggested that the increase in FC may reflect brain processes such as enhanced interoceptive awareness to one’s own bodily state, a neuroplastic change in visual-processing circuits and/or the maintenance of visual spatial memory

mediaWalker: Tracking and browsing news video along the topic thread structure *

ABSTRACT We introduce a news video tracking and browsing interface "mediaWalker" that allows users to explore throughout a news video archive by tracking news topics along a chronological semantic structure of news stories

A Multimodal Constellation Model for Object Image Classification

We present an efficient method for object image classification. The method is an extention of the constellation model, which is a part-based model. Generally, constellation model has two weak points. (1) It is essentially a unimodal model which is unsuitable to be applied for categories with many types of appearances. (2) The probability function that represents the constellation model requires a high calculation cost. We introduced multimodalization and speed-up technique to the constellation model to overcome these weak points. The proposed model consists of multiple subordinate constellation models so that diverse types of appearances of an object category could be described by each of them, leading to the increase of description accuracy and consequently, improvement of the classification performance. In this paper, we present how to describe each type of appearance as a subordinate constellation model without any prior knowledge regarding the types of appearances, and also the implementation of the extended model's learning in realistic time. In experiments, we confirmed the effectiveness of the proposed model by comparison to methods using BoF, and also that the model learning could be realized in realistic time

A Hilbert warping method for handwriting gesture recognition." Pattern Recognition 43.8

a b s t r a c t We propose a novel sequence alignment algorithm for recognizing handwriting gestures by a camera. In the proposed method, an input image sequence is aligned to the reference sequences by phasesynchronization of analytic signals which are transformed from original feature values. A cumulative distance is calculated simultaneously with the alignment process, and then used for the classification. A major benefit of this method is that over-fitting to sequences of incorrect categories is restricted. The proposed method exhibited higher recognition accuracy in handwriting gesture recognition, compared with the conventional dynamic time warping method which explores optimal alignment results for all categories