研究者詳細 - 出口　大輔

論文 - 出口　大輔

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Similar Seasonal-Geo-Region Mining based on Visual Concepts in Social Media Photos 査読有り

Yasutomo Kawanishi, Ichiro Ide, Chen Lu, Takatsugu Hirayama, Keisuke Doman, Daisuke Deguchi, Hiroshi Murase

Proceedings of the 5th IEEE Conference on Multimedia BigData 頁： 86 - 93 2019年9月

Estimation of the attractiveness of food photography based on image features 査読有り

Kazuma Takahashi, Tatsumi Hattori, Keisuke Doman, Yasutomo Kawanishi, Takatsugu Hirayama, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

IEICE Trans. on Information and Systems E102-D 巻 ( 8 ) 頁： 1590 - 1593 2019年8月

Hand Orientation Estimation in Probability Density Form

Kazuaki Kondo, Daisuke Deguchi, Atsushi Shimada

2019年6月

Estimating the Imageability of a sentence for image caption evaluation

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

2019年4月

Estimating the visual variety of concepts by referring to Web popularity 査読有り

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

Multimedia Tools and Applications 78 巻 ( 7 ) 頁： 9463 - 9488 2019年4月

記述言語：英語掲載種別：研究論文（学術雑誌）

Increasingly sophisticated methods for data processing demand knowledge on the semantic relationship between language and vision. New fields of research like Explainable AI demand to step away from black-boxed approaches and understanding how the underlying semantics of data sets and AI models work. Advancements in Psycholinguistics suggest, that there is a relationship from language perception to how language production and sentence creation work. In this paper, a method to measure the visual variety of concepts is proposed to quantify the semantic gap between vision and language. For this, an image corpus is recomposed using ImageNet and Web data. Web-based metrics for measuring the popularity of sub-concepts are used as a weighting to ensure that the image composition in a dataset is as natural as possible. Using clustering methods, a score describing the visual variety of each concept is determined. A crowd-sourced survey is conducted to create ground-truth values applicable for this research. The evaluations show that the recomposed image corpus largely improves the measured variety compared to previous datasets. The results are promising and give additional knowledge about the relationship of language and vision.

DOI： 10.1007/s11042-018-6528-x

他車両からの観測結果を事前知識とした車載カメラ映像中の人物再検出

川西康友, 出口大輔, 井手一郎, 村瀬洋

画像電子学会誌 48 巻 ( 2 ) 頁： 273 - 277 2019年4月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本稿では，過去に別途検出されたことがある人物について，検出した時に得た知識を事前知識として利用することで，その人物を再び検出する際に精度よく検出する「人物再検出」という概念を提案する．また，この概念を車載カメラ映像中の人物検出に適用する方法を示す．本研究では自車がある地点で人物の検出をする際，自車より前にその人物の近くを通過した他車が，先にその場所の近くでその人物を検出している可能性が高いことに着目し，他車による観測を事前知識として人物再検出を行なう．実験により，独自に収集したデータセットを用いた評価において，事前知識を用いることで大きく検出性能が向上することを示す．

Summarization of multiple news videos considering the consistency of audio-visual contents 査読有り

Ye Zhang, Ryunosuke Tanishige, Ichiro Ide, Keisuke Doman, Yasutomo Kawanishi, Daisuke Deguchi, Hiroshi Murase

International Journal of Semantic Computing 13 巻 ( 1 ) 頁： 135 - 155 2019年3月

Hard Negative Mining from in-Vehicle Camera Images based on Multiple Observations of Background Patterns 査読有り

Masashi Hontani, Haruya Kyutoku, David Robert Wong, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 5 巻頁： 435 - 442 2019年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In recent years, the demand for highly accurate pedestrian detectors has increased due to the development of advanced driving support systems.
For the training of an accurate pedestrian detector, it is important to collect a large number of training samples.
To support this, this paper proposes a ``hard negative'' mining method to automatically extract background images which tend to be erroneously detected as pedestrians.
Negative samples are selected based on the assumption that frequent patterns observed multiple times in the same location are most likely parts of the background scene.
As a result of an evaluation using in-vehicle camera images captured along the same route, we confirmed that the proposed method can automatically collect false positive samples accurately.
We also confirmed that a highly accurate detector can be constructed using the additional negative samples.

Next Viewpoint Recommendation by Pose Ambiguity Minimization for Accurate Object Pose Estimation 査読有り

Nik Mohd Zarifie Hashim, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Ayako Amma, Norimasa Kobori

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 5 巻頁： 60 - 67 2019年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

3D object pose estimation by using a depth sensor is one of the important tasks in activities by robots. To reduce the pose ambiguity of an estimated object pose, several methods for multiple viewpoint pose estimation have been proposed. However, these methods need to select the viewpoints carefully to obtain better results. If the pose of the target object is ambiguous from the current observation, we could not decide where we should move the sensor to set as the next viewpoint. In this paper, we propose a best next viewpoint recommendation method by minimizing the pose ambiguity of the object by making use of the current pose estimation result as a latent variable. We evaluated viewpoints recommended by the proposed method and confirmed that it helps us to gain better pose estimation results than several comparative methods on a synthetic dataset.

Pedestrian Intensive Scanning for Active-scan LIDAR 査読有り

Taiki Yamamoto, Fumito Shinmura, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase

Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) 2019 5 巻頁： 313 - 320 2019年2月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In recent years, LIDAR is playing an important role as a sensor for understanding environments of a vehicle’s surroundings. Active-scan LIDAR is being actively developed as a LIDAR that can control the laser irradiation direction arbitrary and rapidly. In comparison with conventional uniform-scan LIDAR (e.g. Velodyne HDL-64e), Active-scan LIDAR enables us to densely scan even distant pedestrians. In addition, if appropriately controlled, this sensor has the potential to reduce unnecessary laser irradiations towards non-target objects. Although there are some preliminary studies on pedestrian scanning strategy for Active-scan LIDARs, in the best of our knowledge, an efficient method has not been realized yet. Therefore, this paper proposes a novel pedestrian scanning method based on orientation aware pedestrian likelihood estimation using the orientation-wise pedestrian’s shape models with local distribution of measured points. To evaluate the effectiveness of the proposed method, we conducted experiments by simulating Active-scan LIDAR using point-clouds from the KITTI dataset. Experimental results showed that the proposed method outperforms conventional methods.

Voting-based Hand-Waving Gesture Spotting from a Low-Resolution Far-Infrared Image Sequence 査読有り

Yasutomo Kawanishi, Chisato Toriyama, Tomokazu Takahashi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Tomoyoshi Aizawa, Masato Kawade

Proceedings of 2018 IEEE International Conference on Visual Communications and Image Processing (VCIP2018) 2018年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

We propose a temporal spotting method of a hand gesture from a low-resolution far-infrared image sequence captured by a far-infrared sensor array. The sensor array captures the spatial distribution of far-infrared intensity as a thermal image by detecting far-infrared waves emitted from heat sources. It is difficult to spot a hand gesture from a sequence of thermal images captured by the sensor due to its low-resolution, heavy noise, and varying duration of the gesture. Therefore, we introduce a voting-based approach to spot the gesture with template matching-based gesture recognition. We confirm the effectiveness of the proposed temporal spotting method in several settings.

DOI： 10.1109/VCIP.2018.8698650

Gaze-inspired Learning for Estimating the Attractiveness of a Food Photo 査読有り

Akinori Sato, Takatsugu Hirayama, Keisuke Doman, Yasutomo Kawanishi, Ichiro Ide, Daisuke Deguchi, Hiroshi Murase

Proceedings of 20th IEEE Int. Symposium on Multimedia (ISM2018) 頁： 36 - 43 2018年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

The number of food photos posted to the Web has been increasing. Most of the users prefer to post delicious-looking food photos. They, however, do not always look delicious. A previous work proposed a method for estimating the attractiveness of food photos, that is, the degree of how much a food photo looks delicious, as an assistive technology for taking a delicious-looking food photo. This method extracted image features from the entire food photo to evaluate the impression. In our work, we conduct a preference experiment where subjects are asked to compare a pair of food photos and measure their gaze. The proposed method extracts image features from local regions selected based on the gaze information and estimates the attractiveness of a food photo by learning regression parameters. Experimental results showed the effectiveness of extracting image features from outside the gaze regions rather than inside them.

DOI： 10.1109/ISM.2018.00015

赤外線センサアレイを用いた畳み込みRNNによる人物行動認識査読有り

川島昂之, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 相澤知禎, 川出雅人

精密工学会誌 84 巻 ( 12 ) 頁： 1025 - 1032 2018年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

This paper proposes a Deep Learning-based action recognition method from an extremely low-resolution FIR image sequence. The method recognizes daily actions by humans (e.g. walking, sitting down, standing up, and so on) and abnormal actions (e.g. falling down) without privacy concerns. While privacy concerns can be ignored, it is difficult to compute feature points and to obtain a clear edge of the human body from an extremely low-resolution FIR image. To address these problems, this paper proposes a Deep Learning-based action recognition method whose inputs are the FIR images and their frame differences cropped by the gravity center of human regions.

低密度LIDAR点群からの歩行者検出査読有り

建部好輝, 出口大輔, 川西康友, 井手一郎, 村瀬洋

精密工学会誌 84 巻 ( 12 ) 頁： 1017 - 1024 2018年12月

記述言語：日本語掲載種別：研究論文（学術雑誌）

In recent years, the demand for pedestrian detection using LIDAR is increasing, as it can be used to prevent traffic accidents involving pedestrians. To avoid traffic accidents, detection of distant pedestrians is very important. However, they are scanned sparsely even if a dense-scan LIDAR is used, and this causes the degradation of the detection accuracy. There-fore, pedestrian detection from sparsely-scanned LIDAR point-clouds is expected to be developed. This paper proposes a LIDAR-based pedestrian detection method using 3DCNN. Since it is difficult to train a 3DCNN directly from sparse point-clouds, the proposed method converts them to a voxel representation using the kernel density estimation based on LIDAR characteristics. To evaluate the performance of the proposed method, an experiment using real-world LIDAR data was conducted. The results showed that the proposed method could detect pedestrians more accurately than detectors trained with other conventional features.

DOI： 10.2493/jjspe.84.1017

Localizing the Gaze Target of a Crowd of People 査読有り

Yuki Kodama, Yasutomo Kawanishi, Takatsugu Hirayama, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase, Hidehisa Nagano, Kunio Kashino

2018年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

What target is focused on by many people?
Analysis of the target is a crucial task, especially in a cinema, a stadium, and so on.
However, it is very difficult to estimate the gaze of each person in a crowd accurately and simultaneously with existing image-based eye tracking methods, since the image resolution of each person becomes low when we capture the whole crowd with a distant camera.
Therefore, we introduce a new approach for localizing the gaze target focused on by a crowd of people.
The proposed framework aggregates the individually estimated results of each person's gaze.
It enables us to localize the target being focused on by them even though each person's gaze localization from a low-resolution image is inaccurate.
We analyze the effects of an aggregation method on the localization accuracy using images capturing a crowd of people in a tennis stadium under the assumption that all of the people are focusing on the same target, and also investigate the effect of the number of people involved in the aggregation on the localization accuracy.
As a result, the proposed method showed the ability to improve the localization accuracy as it is applied to a larger crowd of people.

Analyzing Headlight Flicker Patterns for Improving the Pedestrian Detectability from a Driver 査読有り

Takashi Maeda, Takatsugu Hirayama, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase

Proceedings of 2018 IEEE 21st International Conference on Intelligent Transportation Systems (ITSC2018) 頁： 3113 - 3118 2018年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In this paper, we analyze headlight flicker patterns which improve the pedestrian detectability from a driver. Recently, headlights are becoming capable of selectively projecting light on a pedestrian in addition to the normal forward projection. However, it is still not clear how the light should be
projected to effectively improve the visibility of the pedestrian. We actually analyze nine flicker patterns by controlling duty ratios and durations of lighting time, and conduct experiments in field and laboratory settings. As a result, we reveal that a specific fundamental frequency is effective for improving the pedestrian detectability from a driver. We also conclude that the difference between the two settings are not significant.

Estimating the Scene-wise Reliability of LiDAR Pedestrian Detectors 査読有り

Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Kazuki Kato, Hiroshi Murase

Proceedings of 2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 頁： 3511 - 3516 2018年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Nowadays, development of driving support systems and autonomous driving systems have become active.
Pedestrian detection from in-vehicle sensors is one of the most important technologies for these systems.
However, outputs of pedestrian detectors can not be fully trusted in real environments.
Therefore, we propose an estimation system of pedestrian detector's reliabilities for a given scene.
This paper proposes a scene-wise reliability calculation method for LiDAR-based detectors, and a construction method for their estimators.
Here, the problem is how we can define the reliability.
The proposed method defines the reliability considering oversights as the strictest threshold without oversights.
Meanwhile, it defines the reliability considering false detections as the loosest threshold without false detections.
Experimental results showed that the proposed method could properly represent the reliability of a given scene, and estimate their reliability.

Attribute-aware Semantic Segmentation of Road Scenes for Understanding Pedestrian Orientations 査読有り

Mahmud Dwi Sulistiyo, Yasutomo Kawanishi, Daisuke Deguchi, Takatsugu Hirayama, Ichiro Ide, Jiang-Yu Zheng, Hiroshi Murase

Proceedings of 2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 頁： 2698 - 2703 2018年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Semantic segmentation is an interesting task for many deep learning researchers for scene understanding. However, recognizing details about objects’ attributes can be more informative and also helpful for a better scene understanding in intelligent vehicle use cases. This paper introduces a method for simultaneous semantic segmentation and pedestrian attributes recognition. A modified dataset built on top of the Cityscapes dataset is created by adding attribute classes corresponding to pedestrian orientation attributes. The proposed method extends the SegNet model and is trained by using both the original and the attribute-enriched datasets. Based on an experiment, the proposed attribute-aware semantic segmentation approach shows the ability to slightly improve the performance on the Cityscapes dataset, which is capable of expanding its classes in this case through additional data training.

Estimation of Driver's Insight for Safe Passing based on Pedestrian Attributes 査読有り

Fumito Shinmura, Yasutomo Kawanishi, Daisuke Deguchi, Takatsugu Hirayama, Ichiro Ide, Hiroshi Murase, Hironobu Fujiyoshi

Proceedings of 2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC2018) 頁： 1041 - 1046 2018年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In order to reduce traffic accidents between a vehicle and a pedestrian, recognition of a pedestrian who has a possibility of collision with a vehicle should be helpful. However, since a pedestrian may suddenly change his/her direction and cross the road, it is difficult to predict his/her behavior directly. Here, we focus on the fact that experienced drivers usually pass by a pedestrian while preparing to step on the brake at any moment when they feel danger. If driver assistant systems can estimate such experienced driver’s decisions, they could early detect the pedestrian in danger of collision. Therefore, we classify the driver’s decisions into three types by referring to the accelerator operation of drivers, and propose a method to estimate the type of the driver’s decision. The drivers are considered to decide their actions focusing on various behaviors and states of a pedestrian, namely pedestrian’s attributes. Since the driver’s decisions change along the timeline, the use of a temporal context is considered to be effective. Thus, in this paper, we propose an estimation method using a recurrent neural network architecture with the pedestrian’s attributes as input. We constructed a dataset collected by experienced drivers in control of the vehicle and evaluated the performance, and then confirmed the effectiveness of the use of pedestrian’s attributes.

テレビ会議話者間の視線一致知覚のための目領域合成手法査読有り

井上卓弥, 平山高嗣, 高橋友和, 川西康友, 出口大輔, 井手一郎, 村瀬洋, 黒住隆行, 柏野邦夫

電気学会論文誌C 138 巻 ( 11 ) 頁： 1399 - 1409 2018年11月

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