Shunsuke Kamijo's research while affiliated with The University of Tokyo and other places
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Publications (110)
![Ranker network architectures. a Pairwise ranker [31] during training...](publication/373474373/figure/fig3/AS:11431281187942882@1694451678267/Ranker-network-architectures-a-Pairwise-ranker-31-during-training-phase-b-Proposed_Q320.jpg)
Understanding the driving task-relevant attention (i.e. when to pay more attention?) is beneficial for improved safety in intelligent vehicles. Modeling driving task-relevant attention is challenging because it requires a collective understanding of multiple environmental risk factors in a given traffic scene. We formulate this research problem as...
Lane-level self-localization is essential for autonomous driving. Point cloud maps are typically used for self-localization but are known to be redundant. Deep features produced by neural networks can be used as a map, but their simple utilization could lead to corruption in large environments. This paper proposes a practical map format using deep...
Improving the safety of bicycle riders is one of the critical issues for autonomous driving. The crossing intention of the cyclist is expected to be predicted from the on-board camera of an autonomous vehicle. In a real traffic situation, a cyclist usually turns his or her head to check the situation of the back of him or her before he or she cross...
Recently, autonomous driving technologies require robust perception performance through deep learning with huge data and annotations. To guarantee performance, perception accuracy should be robust even in nighttime. However, lots of perception technologies perform poorly with nighttime data. It is because most current datasets with annotation are c...
Detecting object locations and semantic classes in an image, such as traffic signs, traffic lights, and guide signs, is the crucial problem for autonomous driving, known as object detection. However, stable object detection in complex real-world environments, such as urban environments, is still challenging because of clutter, time of day, blur etc...
![FIGURE 2. The overall flow of radar translation based on Cycle-GAN [13]...](publication/375542262/figure/fig1/AS:11431281204206217@1699622054470/The-overall-flow-of-radar-translation-based-on-Cycle-GAN-13-involves-the-utilization-of_Q320.jpg)
Recently, research on autonomous driving has focused on the advent of various deep learning algorithms. The main sensors for autonomous driving include cameras, LiDAR, and radar, but these algorithms primarily focus on image and LiDAR data. This is because radar data is limited compared to image and LiDAR data. To address the lack of data problem,...
Line drawing is a form of painting that uses lines as expressive elements and often employs the Combination of Abstraction and Figuration (CAF) to enhance artistic expression. However, existing methods tend to focus on generating semantically accurate line drawings, resulting in lackluster images. We observe that, by varying the details of lines in...
In this study, we develop a system to provide information on the sterilization of baggage carts and arriving passenger baggage to airport (Hereafter referred as arrival baggage) by using ultraviolet (UV) sterilization and information communication technology as border quarantine measures at airports. This system sterilizes arrival baggage and bagga...
Recognizing places of interest (POIs) can be challenging for humans, especially in foreign environments. In this study, we leverage smartphone sensors (i.e., camera, GPS) and deep learning algorithms to propose an intelligent solution to recognize POIs in an urban environment. Recent studies have approached landmark recognition as an image retrieva...
Recognizing unfamiliar places is a challenging task for humans. Smartphones equipped with sensors (i.e., camera, GPS) and advancements in computer vision provide various opportunities for creating intelligent solutions. Recent studies have focused on landmark recognition. However, compared to landmarks, points of interest (POI) in urban areas pose...
Transportation Mode Detection (TMD) is an important task for the Intelligent Transportation System (ITS) and Lifelog. TMD, using smartphone built-in sensors, can be a low-cost and effective solution. In recent years, many studies have focused on TMD, yet they support a limited number of modes and do not consider similar transportation modes and hol...
Autonomous driving requires robust and highly accurate perception technologies. Various deep learning algorithms based on only image processing satisfy this requirement, but few such algorithms are based on LiDAR. However, images are only one part of the perceptible sensors in an autonomous driving vehicle; LiDAR is also essential for the recogniti...
Map-based self-localization estimates the pose of the self-driving vehicle in an environment, becoming an essential part of autonomous driving tasks. Generally, maps used in self-localization have detailed geometric information on an environment in formats such as point cloud maps and Gaussian mixture model (GMM) maps. As other maps are widely deve...
Clearly, the year 2021 was a year in which many of us needed to meet, present, discuss and teach from behind our computer screens. Yet, an increasing number of authors are submitting their work to ‘OJ-ITS’, confirming the interest of the ITS community in a Gold Open Access Journal. The number of submissions grew from 44 in 2019–2020 to more than 10...
The driving behavior at urban intersections is very complex. It is thus crucial for autonomous vehicles to comprehensively understand challenging urban traffic scenes in order to navigate intersections and prevent accidents. In this paper, we introduce a stereo vision and 3D digital map based approach to spatially and temporally analyze the traffic...
Understanding the level of environmental risk using vehicle-mounted camera traffic scenes is useful in advanced driver assistance systems (ADAS) to improve vehicle safety. We propose a fast, memory-efficient computer vision based environmental risk perception method using a weakly supervised convolutional neural network-based classifier. We use tra...
A high-definition (HD) map provides structural information for map-based self-localization, enabling stable estimation in real environments. In urban areas, there are many obstacles, such as buses, that occlude sensor observations, resulting in self-localization errors. However, most of the existing HD map-based self-localization evaluations do not...
Pedestrian fatalities and injuries most likely occur in vehicle-pedestrian crashes. Meanwhile, engineers have tried to reduce the problems by developing a pedestrian detection function in Advanced Driver-Assistance Systems (ADAS) and autonomous vehicles. However, the system is still not perfect. A remaining problem in pedestrian detection is the pe...
![Fig. 1: Functional architecture for an autonomous vehicle [5]](profile/Kelvin-Wong-4/publication/350935420/figure/fig1/AS:1128827887591425@1646144949260/Functional-architecture-for-an-autonomous-vehicle-5_Q320.jpg)
![Fig. 3: DFD of autonomous vehicle S. Hernan et. al. [3] define...](profile/Kelvin-Wong-4/publication/350935420/figure/fig3/AS:1128827887599617@1646144949285/DFD-of-autonomous-vehicle-S-Hernan-et-al-3-define-interactor-as-data-provider-and_Q320.jpg)
Stock performance prediction is one of the most challenging issues in time series data analysis. Machine learning models have been widely used to predict financial time series during the past decades. Even though automatic trading systems that use Artificial Intelligence (AI) have become a commonplace topic, there are few examples that successfully...
This article provides a review of the production and uses of maps for autonomous driving and a synthesis of the opportunities and challenges. For many years, maps have helped human drivers make better decisions, and in the future, maps will continue to play a critical role in enabling safe and successful autonomous driving. There are, however, many...
Map-matching based on light detection and ranging (LiDAR) is a promising method for accurate self-localization and recently has gained a wider focus due to the availability of high definition (HD) maps and price-down of LiDARs. In this method, the input scan of the LiDAR is matched to the prebuilt map to get a centimeter-level accuracy position of...
Image based human behavior and activity understanding has been a hot topic in the field of computer vision and multimedia. As an important part, skeleton estimation, which is also called pose estimation, has attracted lots of interests. For pose estimation, most of the deep learning approaches mainly focus on the joint feature. However, the joint f...
A key goal of intelligent vehicles is to provide a safer and more efficient method of transportation. One important aspect of intelligent vehicles is to understand the road scene using vehicle-mounted camera images. Perceiving the level of driving risk of a given road scene enables intelligent vehicles to drive more efficiently without compromising...
Smartphone‐based Lifelog (automatically annotating the users' daily experience from multisensory streams on smartphones) is in great need. Accurate positioning under any situation is one of the most significant techniques for a desirable Lifelog. This paper proposes to detect location‐related activities and use the activity information to improve p...
Accurate localization is an important part of successful autonomous driving. Recent studies suggest that when using map-based localization methods, the representation and layout of real-world phenomena within the prebuilt map is a source of error. To date, the investigations have been limited to 3D point clouds and normal distribution (ND) maps. Th...
Accuracy and time efficiency are two essential requirements for the self-localization of autonomous vehicles. While the observation range considered for simultaneous localization and mapping (SLAM) has a significant effect on both accuracy and computation time, its effect is not well investigated in the literature. In this paper, we will answer the...
![Coverage of OSM tags in Japan 2017 [18].](publication/333937412/figure/tbl1/AS:772392364281859@1561164098935/Coverage-of-OSM-tags-in-Japan-2017-18_Q320.jpg)
Accurately and precisely knowing the location of the vehicle is a critical requirement for safe and successful autonomous driving. Recent studies suggest that error for map-based localization methods are tightly coupled with the surrounding environment. Considering this relationship, it is therefore possible to estimate localization error by quanti...
This paper proposes a smartphone based Driving Data Recorder (DDR). The proposed DDR has the functions of accurate speed estimation and intelligent traffic scene understanding. DDRs are used to store the relevant driving data to provide feedback on driver behavior for accident analysis and insurance issue and so on. The conventional DDRs are standa...
ABS TRACT: Accurate self-localization is a critical problem in the autonomous driving system. In this paper, we proposed a localization system which integrates stereo camera and three-dimensional city model containing building and road mark information. The stereo camera generates visual odometry, reconstructs building scene and detects road mark....
The analysis of customer pose is one of the most important topics for marketing. Using the customer pose information, the retailers can evaluate the customer interest level to the merchandise. However, the pose estimation is not easy because of the problems of occlusion and left-right similarity. To address these two problems, we propose an Integra...
Recently, autonomous vehicle’s self-localization based on the matching of laser scanner data to the high definition (HD) map become more popular due to the availability of HD map and price down of light detection and ranging (LiDAR) technologies. Many types of research have been done to achieve locally and globally accurate HD map for accurate loca...
Accurate pedestrian navigation remains a challenge in urban environments. GNSS receiver behaves poorly because the reflection and blockage of the GNSS signals by buildings or other obstacles. Integration of GNSS positioning and Pedestrian Dead Reckoning (PDR) could provide a more smooth navigation trajectory. However, the integration system cannot...
The analysis of customer pose draws more and more attention of retailers and researchers, because this information can reveal the customer habits and the customer interest level to the merchandise. In the retail store environment, customers’ poses are highly related to their body orientations. For example, when a customer is picking an item from me...
In recent years, traffic congestion, traffic accidents, and deterioration of the environment because of growing population, increasing urbanization, and increasing car ownership have become serious problems in the Asia-Pacific regions. Intelligent transport systems (ITS) are systems that try to solve various road traffic issues using information co...
Accurate vehicle self-localization is significant for autonomous driving. The localization techniques based on Global Navigation Satellite System (GNSS) cannot achieve the required accuracy in urban canyons. On the other hand, simultaneous localization and mapping (SLAM) methods suffer from the error accumulation problem. State-of-the-art localizat...
Today's urban road transport systems experience increasing congestion that threatens the environment and transport efficiency. Global Navigation Satellite System (GNSS)-based vehicle probe technology has been proposed as an effective means for monitoring the traffic situation and can be used for future city development. More specifically, lane-leve...
The accuracy of Mobile Mapping System (MMS), one of the main vehicle-based sensing technologies of the road transportation systems, is significantly degraded due to blockage of GPS signals in deep urban areas which tall buildings are surrounding streets. The current solution, landmark updating technique, takes huge time and human resources, while a...
Precise 3D map as the primary provider of static information such as road geometry and building structures plays an important role for the autonomous vehicles. Access to this map can reduce difficult environment perception problem to a more simple localization problem. Although many vehicle self-positioning techniques are relying on a priori known...
Various applications have utilized a mobile mapping system (MMS) as the main 3D urban remote sensing platform. However, the accuracy and precision of the three-dimensional data acquired by an MMS is highly dependent on the performance of the vehicle’s self-localization, which is generally performed by high-end global navigation satellite system (GN...
The rapid development of road networks in highly urbanized cities requires a substantial number of viaducts to reduce the increasing traffic burden on urban highways. Unfortunately, this road design deteriorates the performance of global positioning system (GPS) navigators due to the signal blockage between satellite and receiver. As a result, it i...
The analysis of customer behavior from surveillance camera is one of the most important open topics for marketing. Traditionally, retailers use the records of cash registers or credit cards to analyze the buying behaviors of customers. However, this information cannot reveal the behaviors of customer when he or she shows interest on the front of th...
Sensors play important roles for autonomous driving. Localization is definitely a key one. Undoubtedly, global positioning system (GPS) sensor will provide absolute localization for almost all the future land vehicles. In terms of driverless car, 1.5 meters of positioning accuracy is the minimum requirement since the vehicle has to keep in a drivin...
Recently, 3D building models have become an important aid to many positioning methods such as LiDAR and GPS positioning. Creating an accurate 3D building model requires accurate 2D building boundaries. We propose a method to correct the horizontal location errors of the 3D building model using GPS measurements. In an urban canyon, several GPS signa...
Accurate vehicle localization technologies are significant for current onboard navigation systems and future autonomous vehicles. More specifically, positioning accuracy is expected at the submeter level. This paper presents an accurate vehicle self-localization system and evaluates the proposed system in different classes of urban environments. Th...