Rui Cao

Rui Cao
The Hong Kong Polytechnic University | PolyU · Department of Land Surveying and Geo-Informatics

Doctor of Philosophy

About

27
Publications
6,482
Reads
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406
Citations

Publications

Publications (27)
Article
Full-text available
Urban land use is key to rational urban planning and management. Traditional land use classification methods rely heavily on domain experts, which is both expensive and inefficient. In this paper, deep neural network-based approaches are presented to label urban land use at pixel level using high-resolution aerial images and ground-level street vie...
Article
With the rapid growing of remotely sensed imagery data, there is a high demand for effective and efficient image retrieval tools to manage and exploit such data. In this letter, we present a novel content-based remote sensing image retrieval (RSIR) method based on Triplet deep metric learning convolutional neural network (CNN). By constructing a Tr...
Article
Urban region function recognition is key to rational urban planning and management. Due to the complex socioeconomic nature of functional land use, recognizing urban region function in high-density cities using remote sensing images alone is difficult. The inclusion of social sensing has the potential to improve the function classification performa...
Article
Although the deep learning-based indoor image localization has made significant improvement in terms of accuracy, efficiency, and storage requirement of large indoor scenes, the need for collecting huge labeled training data severely limits its practical application. Recently, the synthetic images rendered from widely available 3D models have shown...
Article
Accurate and robust short-term bus travel prediction facilitates operating the bus fleet to provide comfortable and flexible bus services. The built environment, including land use, buildings, and public facilities, has an important influence on bus travel demand prediction. However, previous studies regarded the built environment as a static featu...
Article
Full-text available
Timely and accurate socioeconomic indicators are the prerequisite for smart social governance. For example, the level of economic development and the structure of population are important statistics for regional or national policy-making. However, the collection of these characteristics usually depends on demographic and social surveys, which are t...
Article
Full-text available
Timely and accurate maps of fine-grained urban villages (UVs) are essential for rational urban planning, which highlights the importance for automatic recognition methods as alternative to labor-intensive land survey, especially for large cities with high-density urban areas where UV maps cannot be updated frequently. However, it is challenging to...
Article
Cracks in tunnel linings are the most common tunnel defects. As early indicators of structural deterioration, cracks represent critical problems for the safety of tunnels. Several mobile tunnel inspection systems (MTISs) have been developed for tunnel crack inspection. However, due to the weak signals of cracks, these MTISs require considerable exp...
Preprint
Full-text available
Parking demand forecasting and behaviour analysis have received increasing attention in recent years because of their critical role in mitigating traffic congestion and understanding travel behaviours. However, previous studies usually only consider temporal dependence but ignore the spatial correlations among parking lots for parking prediction. T...
Article
Human movements and interactions with cities are characterized by urban mobility networks. Many studies that address urban mobility are inspired by complex networks. The models of complex networks require a large amount of empirical data. However, current works relied on traditional survey data and were unable to take full advantage of the capabili...
Article
City is the place aggregated massive human activities. City is the exchange hub of population flow, goods flow, information flow and currency flow, which is highly dynamic and complex. Smart city provides various tools to acquire spatiotemporal big data, such as satellite and drone remote sensing, mobile sensing, social sensing, crowdsourcing sensi...
Preprint
Full-text available
Estimating depth from RGB images can facilitate many computer vision tasks, such as indoor localization, height estimation, and simultaneous localization and mapping (SLAM). Recently, monocular depth estimation has obtained great progress owing to the rapid development of deep learning techniques. They surpass traditional machine learning-based met...
Article
6DOF camera relocalization is an important component of autonomous driving and navigation. Deep learning has recently emerged as a promising technique to tackle this problem. In this paper, we present a novel relative geometry-aware Siamese neural network to enhance the performance of deep learning-based methods through explicitly exploiting the re...
Article
Accurately locating the fovea is a prerequisite for developing computer aided diagnosis (CAD) of retinal diseases. In colour fundus images of the retina, the fovea is a fuzzy region lacking prominent visual features and this makes it difficult to directly locate the fovea. While traditional methods rely on explicitly extracting image features from...
Article
Predicting depth from a single image is an attractive research topic since it provides one more dimension of information to enable machines to better perceive the world. Recently, deep learning has emerged as an effective approach to monocular depth estimation. As obtaining labeled data is costly, there is a recent trend to move from supervised lea...
Preprint
Predicting depth from a single image is an attractive research topic since it provides one more dimension of information to enable machines to better perceive the world. Recently, deep learning has emerged as an effective approach to monocular depth estimation. As obtaining labeled data is costly, there is a recent trend to move from supervised lea...
Article
Monocular depth estimation plays a crucial role in understanding 3D scene geometry and is a challenging computer vision task. Recently, deep convolutional neural networks have been applied to solve this problem. However, existing methods either directly exploiting RGB pixels which can introduce much noise into the depth map or utilizing over smooth...
Article
Image localization is an important supplement to GPS-based methods, especially in indoor scenes. Traditional methods depending on image retrieval or structure from motion (SfM) techniques either suffer from low accuracy or even fail to work due to the texture-less or repetitive indoor surfaces. With the development of range sensors, 3D colourless m...
Chapter
Image-based geolocalization is an important alternative to GPS-based localization in GPS-denied situations. Among them, ground-to-aerial geolocalization is particularly promising but also difficult due to drastic viewpoint and appearance differences between ground and aerial images. In this paper, we propose a novel spatial-aware Siamese-like netwo...
Preprint
With the rapid growing of remotely sensed imagery data, there is a high demand for effective and efficient image retrieval tools to manage and exploit such data. In this letter, we present a novel content-based remote sensing image retrieval method based on Triplet deep metric learning convolutional neural network (CNN). By constructing a Triplet n...
Preprint
Full-text available
6DOF camera relocalization is an important component of autonomous driving and navigation. Deep learning has recently emerged as a promising technique to tackle this problem. In this paper, we present a novel relative geometry-aware Siamese neural network to enhance the performance of deep learning-based methods through explicitly exploiting the re...
Article
Full-text available
This paper presents a novel indoor topological localization method based on mobile phone videos. Conventional methods suffer from indoor dynamic environmental changes and scene ambiguity. The proposed Visual Landmark Sequence-based Indoor Localization (VLSIL) method is capable of addressing problems by taking steady indoor objects as landmarks. Unl...
Conference Paper
Urban land use is key to rational urban planning and management. Traditional land use classification methods rely heavily on domain experts, which is both expensive and inefficient. In this paper, we explore to utilise deep neural network based approaches to label urban land use at pixel level using high-resolution aerial images and ground-level st...
Article
The existing studies concerning the influence of weather on public transport have mainly focused on the impacts of average weather conditions on the aggregate ridership of public transit. Not much research has examined these impacts at disaggregate levels. This study aims to fill this gap by accounting for intra-day variations in weather as well as...
Article
Full-text available
The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-te...
Article
Full-text available
The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-te...

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Project (1)
Project
urban big data