研究者詳細 - 出口　大輔

講演・口頭発表等 - 出口　大輔

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人物姿勢と注視対象配置制約に基づく後ろ向き人物の注視領域推定

弓矢隼大, 川西康友, 出口大輔, 村瀬洋, 細野峻司

第24回画像の認識・理解シンポジウム(MIRU) 2021年7月30日

歩き方の特徴に着目した所持物の種類・重さ認識の検討

水野雅也, 川西康友, 出口大輔, 村瀬洋, 井下哲夫

第24回画像の認識・理解シンポジウム(MIRU) 2021年7月29日

Pointedness of an Image: Measuring How Pointy an Image is Perceived 国際会議

Chihaya Matsuhira, Marc A. Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

HCII 2021 2021年7月29日

開催年月日： 2021年

記述言語：英語会議種別：ポスター発表

開催地：Virtual

For computers to understand human perception, metrics that can capture human perception well are important. However, there are few metrics that characterize the visual perception of humans towards images. Therefore, in this paper, we propose a novel concept and a metric of pointedness of an image, which describes how pointy an image is perceived. The algorithm is inspired by the Features from Accelerated Segment Test (FAST) algorithm for corner detection which looks on the number of continuous neighboring darker pixels surrounding each pixel. We assume that this number would be proportional to the perceived pointedness in the region around the pixel. We evaluated our method towards how well it could capture the human perception of images. To compare the method with similar metrics that describe shapes, we prepared silhouette images of both artificial shapes and natural objects. The results showed that the proposed method gave nearly equivalent perceptual performance to other metrics and also worked in a larger variety of images.

DOI： https://doi.org/10.1007/978-3-030-78635-9_20

姿勢変化の連続性に着目した人物姿勢推定器の能動学習

森太郎, 出口大輔, 川西康友, 井手一郎, 村瀬洋, 井下哲夫

第24回画像の認識・理解シンポジウム(MIRU) 2021年7月28日

Tell as you imagine: Sentence imageability-aware image captioning 国際会議

Kazuki Umemura, Marc A. Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

27th Int. Conf. on Multimedia Modeling (MMM2021) 2021年6月24日

Imageability Estimation using Visual and Language Features 国際会議

Chihaya Matsuhira, Marc A. Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

2020 International Conference on Multimedia Retrieval 2020年10月28日

開催年月日： 2020年

記述言語：英語会議種別：ポスター発表

開催地：Dublin, Ireland (Virtual)

Imageability is a concept from Psycholinguistics quantizing the human perception of words. However, existing datasets are created through subjective experiments and are thus very small. Therefore, methods to automatically estimate the imageability can be helpful. For an accurate automatic imageability estimation, we extend the idea of a psychological hypothesis called Dual-Coding Theory, that discusses the connection of our perception towards visual information
and language information, and also focus on the relationship between the pronunciation of a word and its imageability. In this research, we propose a method to estimate imageability of words
using both visual and language features extracted from corresponding data. For the estimation, we use visual features extracted from low- and high-level image features, and language features extracted from textual features and phonetic features of words. Evaluations how that our proposed method can estimate imageability more accurately than comparative methods, implying the contribution of each feature to the imageability.

DOI： 10.1145/3372278.3390731

心像性に基づく画像キャプショニングの検討

梅村和紀, カストナーマークアウレル, 井手一郎, 川西康友, 平山高嗣, 道満恵介, 出口大輔, 村瀬洋

メディアエクスペリエンス・バーチャル環境基礎研究会(MVE) 2020年3月5日

開催年月日： 2020年

記述言語：日本語会議種別：口頭発表（一般）

開催地：オンライン

様々な場面や用途に応じた画像キャプショニングを目指し，文の心像性に基づく画像キャプショニング手法を提案する．まず，既存の画像キャプションデータセットを拡張して，様々な抽象度のキャプションをもつ画像キャプションデータセットを構築する．そして，そのデータセット中のキャプションに対して心像性を算出することで，心像性スコア付きキャプションデータセットを構築する．それを用いてキャプショニングモデルを学習し，指定した心像性をもつ画像キャプションを生成する枠組みを構築する．評価実験では，画像キャプションデータセットの拡張の有効性と提案手法による画像キャプショニング実現の可能性を確認した．

料理の種類に応じた盛り付けに関する典型度評価

中村真務, 川西康友, 道満恵介, 平山高嗣, 井手一郎, 出口大輔, 村瀬洋

メディアエクスペリエンス・バーチャル環境基礎研究会(MVE) 2020年3月5日

開催年月日： 2020年

記述言語：日本語会議種別：口頭発表（一般）

開催地：オンライン

本報告では，料理レシピ検索支援を目的として，料理の種類に応じて盛り付けの典型度を評価する手法を提案する．典型的な盛り付けとは，その料理の種類において頻出する特徴を備えている盛りつけである．そこで本研究では，典型的な盛り付けは出現頻度が高いことと，同一の盛り付け同士では似た画像特徴をもつことを考慮して定量的に典型度を推定する．提案手法ではまず，料理写真の背景領域を除去し，色特徴とテクスチャ特徴を抽出する．次に，特徴量を正規化し，カーネル密度推定によって密度分布を生成する．そして，ある料理写真が与えられたとき，その料理写真の特徴量と密度分布から典型度を計算する．評価実験ではカーネル密度推定を用いた典型度評価手法により，色特徴の有効性を確認した．

弱教師あり学習を活用したCyclist検出器の精度向上に関する初期検討

森太郎, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会総合大会 2020年3月3日

同期した注視点の動きに基づく複数対象の注目度推定法の検討

武田一馬, 川西康友, 平山高嗣, 出口大輔, 井手一郎, 村瀬洋, 永野秀尚, 柏野邦夫

電子情報通信学会総合大会 2020年3月3日

複数走行映像を活用した自車位置推定に関する初期検討

後藤優太, 久徳遙矢, 出口大輔, 川西康友, 井手一郎, 村瀬洋

電子情報通信学会総合大会 2020年3月3日

SOANets: Encoder-Decoder based Skeleton Orientation Alignment Network for White Cane User Recognition from 2D Human Skeleton Sequence 国際会議

Naoki Nishida, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Jun Piao

International Conference on Computer Vision Theory and Applications (VISAPP) 2020 2020年2月27日

開催年月日： 2020年

記述言語：英語会議種別：ポスター発表

開催地：Grand Hotel Excelsior Malta

In recent years, various facilities have been deployed to support visually impaired people. However, accidents caused by visual disabilities still occur. In this paper, to support the visually impaired people in public areas, we aim to identify whether a pedestrian image sequence obtained by a surveillance camera indicates the presence of a white cane user by analyzing the temporal transition of a human skeleton represented as 2D coordinates. Our previously proposed method aligns the orientation of the human skeletons to various orientations and identifies a white cane user from the corresponding sequences, relying on multiple classifiers related to each orientation. The method employs an exemplar-based approach to perform the alignment. However, it heavily depends on the number of exemplars and consumes excessive memory. In this paper, we propose a method to align 2D human skeleton representation sequence to various orientations using the proposed Skeleton Orientation Alignment Networks (SOANets) based on an encoder-decoder model. Using SOANets, we can obtain 2D skeleton representation sequences aligned to various orientations, extract richer skeleton features, and recognize white cane users accurately. We conducted an experiment to confirm that the
proposed method improves the recognition rate by 16%, compared to the method that does not use the skeleton
orientation alignment.

Occlusion-Aware Skeleton Trajectory Representation for Abnormal Behavior Detection 国際会議

Onur Temuroglu, Yasutomo Kawanishi, Daisuke Deguchi, Takatsugu Hirayama, Ichiro Ide, Hiroshi Murase, Mayuu Iwasaki, Atsushi Tsukada

The International Workshop on Frontiers of Computer Vision (IW-FCV) 2020年2月20日

開催年月日： 2020年

記述言語：英語会議種別：口頭発表（一般）

開催地：指宿ふれあいプラザなのはな館

Surveillance cameras are expected to play a large role in the development of ITS technologies. They can be used to detect abnormally behaving individuals which can then be reported to drivers nearby. There are multiple works that tackle the problem of abnormal behavior detection. However, most of these works make use of appearance features which have redundant information and are susceptible to noise. While there are also works that make use of pose skeleton representation, they do not consider well how to handle cases with occlusions, which can occur due to the simple reason of pedestrian orientation preventing some joints from appearing in the frame clearly. In this paper, we propose a skeleton trajectory representation that enables handling of occlusions. We also propose a framework for pedestrian abnormal behavior detection that uses the proposed representation and detect relatively hard-to-notice anomalies such as drunk walking. The experiments we conducted show that our method outperforms other representation methods.

Browsing Visual Sentiment Datasets Using Psycholinguistic Groundings 国際会議

Marc Aurel Kastner, Ichiro Ide, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Hiroshi Murase

Lecture Note in Computer Science 2020年1月4日

開催年月日： 2020年

記述言語：英語

開催地：Deajeon Convention Center, Daejeon, Korea

Recent multimedia applications commonly use text and imagery from Social Media for tasks related to sentiment research. As such, there are various image datasets for sentiment research for popular classification tasks. However, there has been little research regarding the relationship between the sentiment of images and its annotations from a multi-modal standpoint. In this demonstration, we built a tool to visualize psycholinguistic groundings for a sentiment dataset. For each image, individual psycholinguistic ratings are computed from the image's metadata. A sentiment-psycholinguistic spatial embedding is computed to show a clustering of images across different classes close to human perception. Our interactive browsing tool can visualize the data in various ways, highlighting different psycholinguistic groundings with heatmaps.

DOI： 10.3758/s13428-018-1099-3

More-Natural Mimetic Words Generation for Fine-Grained Gait Description 国際会議

Hirotaka Kato, Takatsugu Hirayama, Ichiro Ide, Keisuke Doman, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

Lecture Note in Computer Science 2020年1月4日

開催年月日： 2020年

記述言語：英語会議種別：ポスター発表

開催地：Deajeon Convention Center, Daejeon, Korea

A mimetic word is used to verbally express the manner of a phenomenon intuitively. The Japanese language is known to have a greater number of mimetic words in its vocabulary than most other languages. Especially, since human gaits are one of the most commonly represented behavior by mimetic words in the language, we consider that it should be suitable for labels of fine-grained gait recognition. In addition, Japanese mimetic words have a more decomposable structure than these in other languages such as English. So it is said that they have sound-symbolism and their phonemes are strongly related to the impressions of various phenomena. Thanks to this, native Japanese speakers can express their impressions on them briefly and intuitively using various mimetic words. Our previous work proposed a framework to convert the body-parts movements to an arbitrary mimetic word by a regression model. The framework introduced a phonetic space" based on sound-symbolism, and it enabled fine-grained gait description using the generated mimetic words consisting of an arbitrary combination of phonemes. However, this method did not consider the "naturalness" of the description. Thus, in this paper, we propose an improved mimetic word generation module considering its naturalness, and update the description framework. Here, we define the co-occurrence frequency of phonemes composing a mimetic word as the naturalness. To investigate the co-occurrence frequency, we collected many mimetic words through a subjective experiment. As a result of evaluation experiments, we confirmed that the proposed module could describe gaits with more natural mimetic words while maintaining the description accuracy."

DOI： 10.1007/978-3-030-37734-2_18

視覚特徴と言語特徴を用いた単語の心像性推定の検討

松平茅隼, カストナーマークアウレル, 井手一郎, 川西康友, 平山高嗣, 道満恵介, 出口大輔, 村瀬洋

言語処理学会第26回年次大会 2020年3月9日

Modeling Eye-Gaze Behavior of Electric Wheelchair Drivers via Inverse Reinforcement Learning 国際会議

Yamato Maekawa, Naoki Akai, Takatsugu Hirayama, Luis Yoichi Morales, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

2020 IEEE International Conference on Intelligent Transportation Systems 2020年9月21日

開催年月日： 2020年

記述言語：英語会議種別：口頭発表（一般）

開催地：Rhodes, Greece (Virtual)

It is intuitively obvious that eye-gaze behaviors of experienced drivers are different from those of novice drivers. However, it is not easy to understand the difference in their behavior quantitatively. In this work, we present an explainable eye-gaze behavior modeling method for electric wheelchair drivers based on Inverse Reinforcement Learning (IRL). We first create feature maps that represent risk factors during driving. These feature maps are able to represent not only to what but also from where drivers pay attention. IRL uses the feature maps to learn the reward representing the eye-gaze behaviors and allows us to see important features via the automatic acquisition of the reward. Through analysis of the learned model, we show quantitative evidence that eye-gaze behaviors of experienced drivers are better-balanced by paying attention to multiple risks.

DOI： 10.1109/ITSC45102.2020.9294255

俯瞰支援のための文書彩色方法の検討

松平茅隼, カストナーマークアウレル, 井手一郎, 川西康友, 平山高嗣, 道満恵介, 出口大輔, 村瀬洋

メディアエクスペリエンス・バーチャル環境基礎研究会(MVE) 2020年9月9日

開催年月日： 2020年

記述言語：日本語会議種別：口頭発表（一般）

開催地：オンライン

本報告では，小説などの書籍を対象とし，ページ単位でその文書内容に応じた彩色を行なう手法を検討する．このような彩色を施すことにより，書籍をわざわざ開かずとも，読者がその内容の変遷を俯瞰的に知ることができるようになると期待される．提案手法では，文書中に出現する各単語に対して「人間が単語から連想する色」に関する知見を用いて色を割り当てる．そして，各ページにおいて出現確率が高いk色の積み上げ棒グラフを作成し，それらをページ順に並べて表示することで，文書内容の可視化を試みる．最後に，実在する小説を対象にして本手法を適用して定性的な分析を行ない，実際の文書内容に対応付けて本手法の彩色結果を説明できることを確認した．

ソフト順序制約付きラベル境界緩和法に基づく列車前方映像のセマンティックセグメンテーション

振津勇紀, 出口大輔, 川西康友, 井手一郎, 村瀬洋

第23回画像の認識・理解シンポジウム(MIRU) 2020年8月5日

移動する複数物体への群衆からの4次元注目度ヒートマップ生成の初期検討

武田一馬, 川西康友, 平山高嗣, 出口大輔, 井手一郎, 村瀬洋, 永野秀尚, 柏野邦夫

第23回画像の認識・理解シンポジウム（MIRU2020） 2020年8月5日

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