{"title":"Robust and efficient urban scene classification using relative features","authors":"Hai Huang, H. Mayer","doi":"10.1145/2820783.2820872","DOIUrl":"https://doi.org/10.1145/2820783.2820872","url":null,"abstract":"In this paper we present a robust and efficient approach for automatic urban scene classification based on imagery and elevation data. Scene classification is of great interest for a broad spectrum of applications, e.g., city models, urban planning and land cover/use. Because of the availability of high resolution imagery and the corresponding scene complexity as well as heterogeneous appearance of objects, scene classification of urban areas is still challenging with respect to accuracy and efficiency. To this end, we propose \"relative features\", which are intra-class stable and inter-class discriminative, instead of absolute ones for color and geometry to deal with object diversity and scene complexity. The proposed approach provides a pixel-wise as well as a patch-wise schemes with (1) robustness against the variability of object appearance, (2) adaptation to undulating terrain and (3) fully-parallel processing for feature extraction and classification. Experiments on public benchmark and self-acquired data demonstrate the potential of the proposed approach.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123113147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Shahabi, Liyue Fan, Luciano Nocera, Li Xiong, Ming Li
{"title":"Privacy-preserving inference of social relationships from location data: a vision paper","authors":"C. Shahabi, Liyue Fan, Luciano Nocera, Li Xiong, Ming Li","doi":"10.1145/2820783.2820880","DOIUrl":"https://doi.org/10.1145/2820783.2820880","url":null,"abstract":"Social relationships between people, e.g., whether they are friends with each other, can be inferred by observing their behaviors in the real world. Thanks to the popularity of GPS-enabled mobile devices or online services, a large amount of high-resolution location data becomes available for such inference studies. However, due to the sensitivity of location data and user privacy concerns, those studies cannot be largely carried out on individually contributed data without privacy guarantees. Furthermore, we observe that the actual location may not be needed for social relationship studies, but rather the fact that two people met and some statistical properties about their meeting locations, which can be computed in a private manner. In this paper, we envision an extensible framework, dubbed Privacy-preserving Location Analytics and Computation Environment (PLACE), which enables social relationship studies by analyzing individually generated location data. PLACE utilizes an untrusted server and computes several building blocks to support various social relationship studies, without disclosing location information to the server and other untrusted parties. We present PLACE with three example social relationship studies which utilize four privacy-preserving blocks with encryption and differential privacy primitives. The successful realization of PLACE will facilitate private location data acquisition from individual devices, thanks to the strong privacy guarantees, and will enable a wide range of applications.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125802880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Towards truly ubiquitous indoor localization on a worldwide scale","authors":"M. Youssef","doi":"10.1145/2820783.2820883","DOIUrl":"https://doi.org/10.1145/2820783.2820883","url":null,"abstract":"Although GPS has been considered a ubiquitous outdoor localization technology, we are still far from a similar technology for indoor environments. While a remarkable effort has been put in developing indoor location determination systems, they are still isolated efforts that are tailored to specific deployments. A truly ubiquitous indoor positioning system is envisioned to be deployed on a large scale worldwide, with minimum overhead, to work with heterogeneous devices, and to allow users to roam seamlessly from indoor to outdoor environments. Such a system will enable a wide set of applications including worldwide seamless direction finding between indoor locations, enhancing first responders' safety by providing anywhere localization and floorplans, and providing a richer environment for location-aware social networking applications. We describe an architecture for the ubiquitous indoor positioning system and the multi-disciplinary challenges that have to be addressed to materialize it. We also discuss the current pioneering efforts in the research community towards realizing this goal.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125904531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antonio Rodriguez Cervilla, S. Tabik, L. F. Romero
{"title":"3D-viewshed map: a measure of landscape deepness","authors":"Antonio Rodriguez Cervilla, S. Tabik, L. F. Romero","doi":"10.1145/2820783.2820865","DOIUrl":"https://doi.org/10.1145/2820783.2820865","url":null,"abstract":"The 3D perception of the human eye is more impressive in irregular than in flat landscapes. Current visibility computation algorithms in Geographic Information Systems (GIS) are based on the concept of 2D-viewshed. Extending these methods to 3D space is too expensive computationally. This paper presents the first approach to compute total 3D-viewshed maps on Digital Elevation Models (DEMs). The paper provides the first total 3D-viewshed map together with a comparative study of total 2D-viewshed versus total 3D-viewshed maps.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"22 21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123421154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Grooming big data from afar","authors":"P. Baumann, A. Dumitru, Vlad Merticariu","doi":"10.1145/2820783.2820854","DOIUrl":"https://doi.org/10.1145/2820783.2820854","url":null,"abstract":"Flexible, scalable services on massive geo data receive much attention today. In particular, the OGC Web Coverage Service (WCS) standards suite has established a best practice for versatile access and retrieval on spatio-temporal \"Big Data\". Fewer efforts have been devoted, though, to an easy-to-use, standardized way of maintaining a service's offering. Our experience from supporting a series of heterogeneous, large-scale services reveals that this can become tedious indeed, due to heterogeneity and incompleteness of incoming data, operator-less transformation and ingest of large amounts of files, as well as the need for narrowly focused manual corrections and updates sometimes. In this contribution, we present the WCS-T (for \"Transaction\") specification which enables users and machines to perform atomic insertion, updating, and deletions through simple Web requests. WCS-T has been implemented and is actively being used in projects; recently, it has entered the adoption process in OGC to become part of the WCS suite.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"9 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123573649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaofeng Xu, Li Xiong, V. Sunderam, Jinfei Liu, Jun Luo
{"title":"VPIndexer","authors":"Xiaofeng Xu, Li Xiong, V. Sunderam, Jinfei Liu, Jun Luo","doi":"10.1145/2820783.2820786","DOIUrl":"https://doi.org/10.1145/2820783.2820786","url":null,"abstract":"Indexing moving objects has been extensively studied in the past decades. In most real world applications, the moving objects exhibit particular patterns on their velocities. For example, velocities of vehicles in city road networks usually show patterns on both directions and values. Velocity-based partitioning techniques have been proved effective in improving query performances of moving object indexes. This demo presents VPIndexer, a toolkit for visualizing comparison of three velocity-based partitioning algorithms: VMBR-based partitioning, DVA-based partitioning and our recently proposed speed-based partitioning techniques. VPIndexer uses the Bx-tree and the TPR*-tree as the baseline approaches.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114439046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. P. Magalhães, Gustavo Coutinho, J. Macêdo, Camila Ferreira, L. A. Cruz, M. Nascimento
{"title":"Graphast: an extensible framework for building applications on time-dependent networks","authors":"R. P. Magalhães, Gustavo Coutinho, J. Macêdo, Camila Ferreira, L. A. Cruz, M. Nascimento","doi":"10.1145/2820783.2820791","DOIUrl":"https://doi.org/10.1145/2820783.2820791","url":null,"abstract":"Graphast is a framework tool that allows developers to compose a number of network models, data importing/exporting services as well as query services, in order to quickly build applications on time-dependent networks. The main goal is to allow developers to implement solutions to different types of problems on time-dependent networks using spatial queries, such as nearest neighbor queries, optimal sequenced routes, etc. Graphast allows the combination of facilities provided by the framework via a public API and/or the building of new facilities, e.g., a new query processing algorithm, and incorporate those into Graphast for others to use them as well. In this paper, we discuss Graphast's architectural components and how one can create/store instances of those components in order to build an application. The steps necessary for building a real world application are also presented.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116592060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Berkhin, Michael R. Evans, Florin Teodorescu, Wei Wu, Dragomir Yankov
{"title":"A new approach to geocoding: BingGC","authors":"P. Berkhin, Michael R. Evans, Florin Teodorescu, Wei Wu, Dragomir Yankov","doi":"10.1145/2820783.2820827","DOIUrl":"https://doi.org/10.1145/2820783.2820827","url":null,"abstract":"Real-time geocoders help users find precise locations in online mapping systems. Geocoding unstructured queries can be difficult, as users may describe map locations by referencing several spatially co-located entities (e.g., a business near a street intersection). Serving these queries is important as it provides new capabilities and allows for expanding in markets with less structured postal systems. Traditionally, this problem poses significant difficulties for online systems where latency constraints prevent exhaustive join-based algorithms. Previous work in this area involved natural language processing to segment queries based on known rules, or purely spatial approaches that are difficult to maintain and may have high latency. In this paper, we present a new approach to geocoding - BingGC - that makes fulfillment of extremely diverse geocoding queries possible via a combination of traditional web search technologies and a novel algorithm that uses textual search and spatial joins to quickly find results. It allows resolution of up to s spatially co-located entities in a single query with no pre-computation or rule-based matching. We provide experimental analysis of our system compared against leading online geocoders.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129423133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A mobile trusted path system based on social network data","authors":"F. Mata, Christophe Claramunt","doi":"10.1145/2820783.2820799","DOIUrl":"https://doi.org/10.1145/2820783.2820799","url":null,"abstract":"Social networks provide rich data sources for analyzing people journeys in urban environments. This paper introduces a trusted path system that helps users to find their routes based in two criteria: low crime rate and no theft report. These data are obtained from two complementary sources: geo-tagged tweets from the social network Twitter, and an official database given by the Police of Mexico City. Recommended paths are computed automatically from these data sources by a complementary application of social mining techniques, Bayes algorithm and an adaptation of the Dijkstra algorithm. This system can be also used to identify the probability that an event occurs in specific locations and times. A proof of concept of the system is illustrated through two example scenarios.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123207919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A calibration-free RF localization system","authors":"R. Elbakly, M. Youssef","doi":"10.1145/2820783.2820853","DOIUrl":"https://doi.org/10.1145/2820783.2820853","url":null,"abstract":"We present the design, implementation, and evaluation of NaviRize: a novel system that can provide calibration-free, accurate RF-based indoor localization that works in realistic environments on heterogeneous devices. NaviRize is based on the space partitioning of the installed RF Transmitters (RFTXs) and exploits constraints based on the mutual Received Signal Strength(RSS) relation between each pair of RFTXs to further enhance the estimated user location. Evaluation of NaviRize shows that it can achieve a consistent median accuracy of 2.8m under different scenarios.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121591729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}