Nobuo Kawaguchi

• Dr. Eng.
• Professor at Nagoya University

The manual creation of a ceiling plan consumes many human resources to confirm the current state of existing buildings for renovation. Identifying the positions and the types of existing fixtures is crucial for drawing a ceiling plan. Therefore, to assist in drawing a ceiling plan, an efficient method that generates a reliable photorealistic whole...

We publicly release OpenUAS, a dataset of area embeddings based on urban usage patterns, including embeddings for over 1.3 million 50-meter square meshes covering a total area of 3,300 square kilometers. This dataset is valuable for analyzing area functions in fields such as market analysis, urban planning, transportation infrastructure, and infect...

This study explores the feasibility of dialogue systems with individuality capable of providing continuous and lasting assistance via a multiple device dialogue system. A framework has been devised to manage dialogue history, allowing for the use of a singular identity across various interfaces, including chatbots and virtual avatars. This framewor...

The COVID-19 pandemic, which began in 2020, has changed people’s lives, and people are shopping more online. While the analysis of online shopping is becoming increasingly important, regional differences in consumption trends exist. This study proposes a data-driven regional modeling method based on EC purchase data to examine the regional characte...

This research proposes a communication system called Mobility Link XR that connects physical space and cyberspace with mobility. Mobility Link XR is a system that enables remote users to view panoramic video from a 360-degree camera attached to a mobility vehicle in different space by wearing a VR device, and mobility users to view the remote user...

AI-driven Action Quality Assessment (AQA) of sports videos can mimic Olympic judges to help score performances as a second opinion or for training. However, these AI methods are uninterpretable and do not justify their scores, which is important for algorithmic accountability. Indeed, to account for their decisions, instead of scoring subjectively,...

Various types of indoor positioning methods have been proposed. Accordingly, various ground-truth measurement methods have also been used. The selection of the ground-truth measurement method is crucial when appropriately evaluating the indoor positioning methods. In recent years, data-driven methods have been actively proposed, making the ground-t...

Emotions are essential for constructing social relationships between humans and interactive systems. Although emotional and empathetic dialogue generation methods have been proposed for dialogue systems, appropriate dialogue involves not only mirroring emotions and always being empathetic but also complex factors such as context. This paper propose...

Dialogue systems that handle emotions have been shown to improve user satisfaction and increase positive interactions, and are expected to play a role as a digital partner that accompanies humans. In order for dialogue systems to recognize user emotions and express their own emotions, emotion regulation methods that select appropriate emotions from...

Workloads in logistics warehouses have been increasing to meet growing demand, and a labor shortage has become a problem. Utilizing information of laborer locations leads to an increase in productivity. We propose an integrated positioning method using solar-powered Bluetooth Low Energy (BLE) beacons. They are easy to install and maintenance-free s...

Cooperative perception is a prospective application to improve road safety by having connected autonomous vehicles (CAVs) exchange their raw or processed sensor data over vehicular communications. Since CAVs heavily rely on sensor-based perception, including vision cameras, LiDARs, and radars, cooperative perception has an immense potential to impr...

The implementation of wearable airbags to prevent fall injuries depends on accurate pre-impact fall detection and a clear distinction between activities of daily living (ADL) and them. We propose a novel pre-impact fall detection algorithm that is robust against ambiguous falling activities. We present a data-driven approach to estimate the fall ri...

Recently, there has been an increasing demand for traffic simulation and congestion prediction for urban planning, especially for infection simulation due to the Covid-19 epidemic. On the other hand, the widespread use of wearable devices has made it possible to collect a large amount of user location history with high accuracy, and it is expected...

Autonomous Mobile Robots (AMRs), including delivery robots, security robots, and automated wheelchairs, are very promising to improve the quality of life, safety, mobility, and productivity. To deploy such sensor-rich AMRs in the real-world society, we have to resolve not only technical challenges but also ethical and societal issues. In addition,...

In this research, we proposed an active management method to monitor more autonomous vehicles (AVs) remotely with few observers. A management system is created to get the status from the AVs and separate the monitoring requirement to the observers optimally. When the requirements might be intensive, the management system can adjust the movements of...

In the last two decades, researchers have investigated dance performance using activity recognition methods. However, most of the works did not focus on dance figures. Learning ballroom dance figures, a completed set of footsteps, makes it difficult for less experienced dancers. Hence, the paper presents a classification method of ballroom dance fi...

Human-robot collaboration and cooperation are critical for Autonomous Mobile Robots (AMRs) in order to use them in indoor environments, such as offices, hospitals, libraries, schools, factories, and warehouses. Since a long transition period might be required to fully automate such facilities, we have to deploy AMRs while improving safety in the mi...

Mixed reality (MR) technology has been attracting attention in the automobile industry and logistics industry for work training and remote work support for newcomers. However, work support using MR technology has the problem that displaying too much information obstructs the user’s field of vision and rather interferes with the work. Therefore, it...

The spread of mobile phones made it easy to estimate person-flow for corporate marketing, crowd analysis, and countermeasures for disaster and disease. However, due to recent privacy concerns, regulations have been tightened around the world and most smartphone operating systems have increased privacy protection. To solve this, in this study, we pr...

The paper presents a ballroom dance figure classification method with LSTM using video and wearable sensors. Ballroom dance is a popular sport among people regardless of age or sex. However, learning ballroom dance is very difficult for less experienced dancers as it has many complex types of “dance figures”, which is a completed set of footsteps....

This paper proposes an indoor localization method for Bluetooth Low Energy (BLE) devices using an end-to-end LSTM neural network. We focus on a large-scale indoor space where there is a tough environment for wireless indoor localization due to signal instability. Our proposed method adopts end-to-end localization, which means input is a time-series...

We present a new model for encouraging people to get involved with monitoring and taking part in the life of cities. Cities could be smarter if IoT and people could serve as engaged and pro-active data resources (i.e., crowd sensing). This study tackles two challenges: methods by which the privacy of people who act as sensors/actuators can be guara...

Bus transportation service is more influenced than other public transport by various factors such as traffic congestion, weather condition, number of passengers, traffic signals. These factors often cause delay and the users may feel inconvenience while waiting at the bus stop. In the case of snowfall event, a large delay occurs, which greatly redu...

There is an inherent problem of error accumulation in Pedestrian Dead Reckoning (PDR). In this chapter, we introduce a PDR error compensation scheme based on the assumption that can obtain sparse locations. Sparse locations are discontinuous locations obtained by using an absolute localization method or passage detection devices (ex. RFID tag, BLE...

There are many inertial sensor based indoor localization methods for smartphone, for example, SINS and PDR. How-ever, most of the MEMS sensors of smartphones are not precise enough for these methods. We proposed end-to-end walking speed estimation method using deep learning to perform robust walking speed estimation with a low-precision sensor. Cur...

The paper presents a hybrid ballroom dance step type recognition method using video and wearable sensors. Learning ballroom dance is very difficult for less experienced dancers as it has many complex types of steps. Therefore, our purpose is to recognize the various step types to support step learning. While the major approach to recognize dance pe...

Bus transportation service is more strongly influenced than other public transport modalities by various factors such as traffic congestion, weather conditions, number of passengers, and traffic signals. These factors often cause delays, and users may feel inconvenienced when waiting at a bus stop. Few studies have analyzed the relationship between...

Public transport bus service is an important means of transportation for commuting, schooling and daily life. However, many unpredictable problems arise, resulting in delays caused by traffic congestion or an increased number of passengers. Changing the operation schedule may alleviate these problems; however, determining the optimal schedule chang...

We propose an integrated framework for sensing, recognizing and utilizing of subjective time as context. Various studies on experimental psychology have showed several factors which affects subjective time. Those factors should be partially captured by ubiquitous sensors such as smartphones and wearable devices, therefore, we tackle to create commo...

This paper proposes an accurate estimation method of walking speed using deep learning for smartphone-based Pedestrian Dead Reckoning (PDR).PDR requires to estimate speed and direction of pedestrians accurately using accelerometer and gyroscope.To improve the accuracy of PDR, existing works focused to improve the key factors of speed estimation (i....

In this paper, LSTM-based neural network is applied to indoor localization using mobile BLE tag's signal strength collected by multiple scanners. Stability of signal strength is a critical factor of wireless indoor localization for higher accuracy. While traditional methods like trilateration and fingerprinting suffer from noise and packet loss, de...

This paper proposes a novel method of estimating the absolute scale of monocular SfM for a multi-modal stereo camera. In the fields of computer vision and robotics, scale estimation for monocular SfM has been widely investigated in order to simplify systems. This paper addresses the scale estimation problem for a stereo camera system in which two c...

Inspection and repair of road infrastructures are important for safety. While highways and motorways are periodically inspected with specialized vehicles, the roads which are maintained by local governments are not inspected because of lack of budget and workforce. In the future, however, a large number of autonomous driving cars will run everywher...

In recent years, the importance of location information has increased due to the popularization of terminals such as smartphones. Our purpose is to estimate the 3D position of smartphones within several centimeters. This location information can reveal a person's behavior patterns and subject of interest. A method based on dynamic magnetism can est...

Activity recognition has emerged as a challenging and high-impact research field, as over the past years smaller and more powerful sensors have been introduced in wide-spread consumer devices. Validation of techniques and algorithms requires large-scale human activity corpuses and improved methods to recognize activities and the contexts in which t...

This paper proposes a novel method of estimating the absolute scale of monocular SfM for a multi-modal stereo camera. In the fields of computer vision and robotics, scale estimation for monocular SfM has been widely investigated in order to simplify systems. This paper addresses the scale estimation problem for a stereo camera system in which two c...

The bases of the approaches of UCLab(submission 1) towards SHL recognition challenge are using Random Forest and letting it select important features. Using accelerometer, gyroscope, magnetometer, gravity and pressure sensor as input data, features such as mean, variance, max, difference of max and min, and main frequency are calculated. We find th...

For high precision estimation with SHL recognition challenge, we use a deep learning framework based on convolutional layers and LSTM recurrent units (ConvLSTM). We, UCLab(submission 2), propose the model combined two different ConvLSTMs. One ConvLSTM of convolution layers has large kernel size and the other has small kernel size. We expect that th...

We address automatic matching of street images with relevant web resources to enable identification of store signage in street images. Identification methods for signage usually involve image matching, which attempts to match query images to other similar viewings using pre-labeled copies from a target dataset. Manual target dataset such as a finge...

This paper presents a novel method for detecting scene changes from a pair of images with a difference of camera viewpoints using a dense optical flow based change detection network. In the case that camera poses of input images are fixed or known, such as with surveillance and satellite cameras, the pixel correspondence between the images captured...

In this paper, we propose a method for cloud removal from visible light RGB satellite images by extending the conditional Generative Adversarial Networks (cGANs) from RGB images to multispectral images. Satellite images have been widely utilized for various purposes, such as natural environment monitoring (pollution, forest or rivers), transportati...

We have developed an indoor location estimation method using mobile Bluetooth Low Energy (BLE) tags carried by people and BLE scanners fixed to a building. By using the method, we can analyze the behavior of the attendees at some large-scale exhibition, such as the order of the visited booth and the duration of the stay. Using mobile BLE tags has s...

Technological advances enable the inclusion of miniature sensors (e.g., accelerometers, gyroscopes) on a variety of wearable/portable information devices. Most current devices utilize these sensors for simple orientation and gesture recognition only. However, in the future the recognition of more complex and subtle human behaviors from these sensor...

One of the indoor localization methods utilizing accelerometer and gyroscope is called PDR (Pedestrian Dead Reckoning). Various schemes have been proposed in PDR, however, sufficient precision has not been achieved because of the error accumulation. In this research, we propose a PDR error compensation scheme based on an assumption that can obtain...

This paper presents a novel method for fully automatic and convenient extrinsic calibration of a 3D LiDAR and a panoramic camera with a normally printed chessboard. The proposed method is based on the 3D corner estimation of the chessboard from the sparse point cloud generated by one frame scan of the LiDAR. To estimate the corners, we formulate a...

This paper presents a novel method for fully automatic and convenient extrinsic calibration of a 3D LiDAR and a panoramic camera with a normally printed chessboard. The proposed method is based on the 3D corner estimation of the chessboard from the sparse point cloud generated by one frame scan of the LiDAR. To estimate the corners, we formulate a...

In this paper, we propose a method for cloud removal from visible light RGB satellite images by extending the conditional Generative Adversarial Networks (cGANs) from RGB images to multispectral images. Satellite images have been widely utilized for various purposes, such as natural environment monitoring (pollution, forest or rivers), transportati...

Nearby event data, such as those for exhibitions and sales promotions, may help users spend their free time more efficiently. However, most event data are hidden in millions of webpages, which is very time-consuming for a user to find such data. To address this issue, we use web mining that extracts event data from webpages. In this paper, we propo...

Techniques for obtaining customers' behavior (dwell time, count, and flow) in a shopping mall or large exhibit are highly sought-after by organizers or shop owners. Additionally, ways of effectively directing customers from cyber space such as the Web or smartphone apps to physical retail stores are also in high demand. "Online to Offline (O2O) Mar...

Indoor location estimation is essential technology when we analyse the participants' activities in large-scale exhibition. There are some problems with existing methods such as PDR, ultrasound and laser range finder: installation location of measurement equipment at large site, cost for measurement equipment, and necessity of smartphone application...

The segmentation of point clouds is an important aspect of automated processing tasks such as semantic extraction. However, the sparsity and non-uniformity of the point clouds gathered by the popular 3D mobile LiDAR devices pose many challenges for existing segmentation methods. To improve the segmentation results of point clouds from mobile LiDAR...

There are many methods for indoor positioning. These methods are divided into the relative localization and absolute localization. In the relative localization, one widely used method is Pedestrian Dead Reckoning (PDR). Relative localization estimates the moving distance, orientation, and height of the pedestrian. However, relative localization has...

PDR (Pedestrian Dead Reckoning) is a very promising technology for indoor positioning. We held a technical challenge, entitled the UbiComp/ISWC 2015 PDR Challenge, consisting of the following three categories: a PDR algorithm category; a PDR Evaluation method category; and an exhibition. In this paper, we especially focus on several systems for the...

Some people cannot effectively utilize pedestrian navigation systems due to their limited spatial ability. To provide guidance in consideration of an individual's spatial ability, measuring spatial ability is necessary. In this paper, we propose measurement methods for spatial ability using a virtual reality system. We studied spatial ability in te...

A highly accurate estimation method of 3-D pedestrian trajectories from walking activity sensing data is proposed. This method uses data from an accelerometer, a gyrometer, and an air pressure sensor, and does not require detailed information on the building structure. In activity sensing using wearable sensors, higher accuracy can be expected from...

PDR (Pedestrian Dead Reckoning) is a very promising technology for indoor positioning. We held a technical challenge, entitled the UbiComp/ISWC 2015 PDR Challenge, consisting of the following three categories: Algorithm, Evaluation, and Exhibition. In this paper, we specially focus on collected data for PDR algorithm category. UbiComp/ISWC particip...

Human activity recognition by wearable sensors will enable a next-generation human-oriented ubiquitous computing. However, most of the existing research on human activity recognition is based on a small number of subjects, and lab-created-data. To overcome this problem, we hold HASC Challenge as a technical challenge to collect the data for activit...

We present a scheme that improves accuracy of 2.4GHz RF tag based indoor positioning. The accuracy of indoor positioning using 2.4GHz RF tags is affected by propagation loss caused by human body shielding, especially in crowded situations. This paper proposes a RSSI compensation scheme that estimate a crowd density level based on detected 2.4 GHz R...

Current motion sensors in wearable devices are primarily used for simple orientation and motion sensing. They provide however signals related to more complex and subtle human behaviours which will enable next-generation human-oriented computing in scenarios of high societal value. This requires large scale human activity corpuses and improved metho...

We propose Landmark-Conscious Voice Navigation as one type of a pedestrian navigation system, which navigate users by only voice guidance. It is necessary to standardize data model in order to use this system widely. In a previous paper[1], we constructed a basic voice navigation system, which uses Open Street Map based data model. In this paper, a...

In this work, we implement a mobile system called Velobug to measures 3D data of the environment. Velobug could generate dense and colored point cloud to reconstruct the environment for 3D mapping with long effective range. Velobug is mainly consisted of a Velodyne HDL-32e LiDAR senor and a Point Grey Research Ladybug3 panoramic camera. The LiDAR s...

Since the advent of smartphones equipped with sophisticated sensing hardware, human activity recognition research has moved from utilizing dedicated sensing devices to using commercial smartphones. This paper presents the design of an algorithm to recognize and estimate travel distance when riding an elevator and its corresponding implementation wi...

The passage event on the specific spot is one of the useful information for position estimate. If we can detect the passage of the specific spot, we could contribute to the field of the position estimate because it is available for movement course identification, and the correction of the position estimate error. We suggest pedestrian passage detec...

Recent advancement of technology enables installations of small sized accelerometers or gyroscopes on various kinds of wearable/portable information devices. By using such wearable sensors, these devices can estimate its posture or status. However, most of current devices only utilize these sensors for simple orientation and gesture recognition. Mo...