15.3.3.10 Traffic Lights, Objects along the Road, Inspections

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Mobile Digital Cameras for As-Built Surveys of Roadside Features,
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Alessandretti, G., Broggi, A., Cerri, P.,
Vehicle and Guard Rail Detection Using Radar and Vision Data Fusion,
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IEEE DOI 0703
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Lopez-Sastre, R.J., Renes-Olalla, J., Gil-Jimenez, P., Maldonado-Bascon, S., Lafuente-Arroyo, S.,
Heterogeneous Visual Codebook Integration Via Consensus Clustering for Visual Categorization,
CirSysVideo(23), No. 8, 2013, pp. 1358-1368.
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Clustering algorithms. category-level object and activity recognition. BibRef

Joo, S.K.[Sung-Kwan], Kim, Y.[Yongkwon], Cho, S.I.[Seong Ik], Choi, K.H.[Kyoung-Ho], Lee, K.S.[Ki-Sung],
Traffic Light Detection Using Rotated Principal Component Analysis for Video-Based Car Navigation System,
IEICE(E91-D), No. 12, December 2008, pp. 2884-2887.
DOI Link 0804
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Roters, J., Jiang, X., Rothaus, K.,
Recognition of Traffic Lights in Live Video Streams on Mobile Devices,
CirSysVideo(21), No. 10, October 2011, pp. 1497-1511.
IEEE DOI 1110
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Schwarzbach, F.[Friederike],
Suitability of Different LIDAR Data Sets for 3D Mapping of the Road Environment,
PFG(2009), No. 2, 2009, pp. 117-127.
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Cabo, C., Ordoñez, C., García-Cortés, S., Martínez, J.,
An algorithm for automatic detection of pole-like street furniture objects from Mobile Laser Scanner point clouds,
PandRS(87), No. 1, 2014, pp. 47-56.
Elsevier DOI 1402
Urban BibRef

Yu, Y.T.[Yong-Tao], Li, J.[Jonathan], Guan, H.Y.[Hai-Yan], Wang, C.[Cheng], Yu, J.[Jun],
Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds,
GeoRS(53), No. 3, March 2015, pp. 1374-1386.
IEEE DOI 1402
feature extraction
See also Automated Detection of Three-Dimensional Cars in Mobile Laser Scanning Point Clouds Using DBM-Hough-Forests.
See also Marked Point Process for Automated Tree Detection from Mobile Laser Scanning Point Cloud Data, A.
See also Semi-Automated Extraction and Delineation of 3D Roads of Street Scene from Mobile Laser Scanning Point Clouds.
See also Capsule-Based Networks for Road Marking Extraction and Classification from Mobile LiDAR Point Clouds.
See also Rapid Extraction of Urban Road Guardrails from Mobile LiDAR Point Clouds. BibRef

Wu, F.[Fan], Wen, C.L.[Cheng-Lu], Guo, Y.L.[Yu-Lan], Wang, J.J.[Jing-Jing], Yu, Y.T.[Yong-Tao], Wang, C.[Cheng], Li, J.[Jonathan],
Rapid Localization and Extraction of Street Light Poles in Mobile LiDAR Point Clouds: A Supervoxel-Based Approach,
ITS(18), No. 2, February 2017, pp. 292-305.
IEEE DOI 1702
Feature extraction BibRef

Gao, J.L.[Jian-Lan], Chen, Y.P.[Yi-Ping], Junior, J.M.[José Marcato], Wang, C.[Cheng], Li, J.[Jonathan],
Rapid Extraction of Urban Road Guardrails from Mobile LiDAR Point Clouds,
ITS(23), No. 2, February 2022, pp. 1572-1577.
IEEE DOI 2202
Roads, Laser radar, Shape, Rough surfaces, Surface roughness, Clustering algorithms, Light detection and ranging, road guardrails
See also Capsule-Based Networks for Road Marking Extraction and Classification from Mobile LiDAR Point Clouds.
See also Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds. BibRef

Seo, Y., Lee, J., Zhang, W., Wettergreen, D.,
Recognition of Highway Workzones for Reliable Autonomous Driving,
ITS(16), No. 2, April 2015, pp. 708-718.
IEEE DOI 1504
Detectors BibRef

Suhr, J.K., Jung, H.G.,
Dense Stereo-Based Robust Vertical Road Profile Estimation Using Hough Transform and Dynamic Programming,
ITS(16), No. 3, June 2015, pp. 1528-1536.
IEEE DOI 1506
Databases BibRef

Shi, Z., Zou, Z., Zhang, C.,
Real-Time Traffic Light Detection With Adaptive Background Suppression Filter,
ITS(17), No. 3, March 2016, pp. 690-700.
IEEE DOI 1603
Feature extraction BibRef

Mascetti, S.[Sergio], Ahmetovic, D.[Dragan], Gerino, A.[Andrea], Bernareggi, C.[Cristian], Busso, M.[Mario], Rizzi, A.[Alessandro],
Robust traffic lights detection on mobile devices for pedestrians with visual impairment,
CVIU(148), No. 1, 2016, pp. 123-135.
Elsevier DOI 1606
Assistive technologies
See also ZebraRecognizer: Pedestrian crossing recognition for people with visual impairment or blindness. BibRef

Jensen, M.B.[Morten B.], Philipsen, M.P.[Mark P.], Møgelmose, A., Moeslund, T.B.[Thomas B.], Trivedi, M.M.[Mohan M.],
Vision for Looking at Traffic Lights: Issues, Survey, and Perspectives,
ITS(17), No. 7, July 2016, pp. 1800-1815.
IEEE DOI 1608
filtering theory BibRef

Jensen, M.B.[Morten B.], Philipsen, M.P.[Mark P.], Moeslund, T.B.[Thomas B.], Trivedi, M.M.[Mohan M.],
Comprehensive Parameter Sweep for Learning-Based Detector on Traffic Lights,
ISVC16(II: 92-100).
Springer DOI 1701
BibRef

Jensen, M.B.[Morten B.], Nasrollahi, K., Moeslund, T.B.[Thomas B.],
Evaluating State-of-the-Art Object Detector on Challenging Traffic Light Data,
Traffic17(882-888)
IEEE DOI 1709
Data models, Detectors, Image color analysis, Predictive models, Shape, Training, Training, data BibRef

Jensen, M.B.[Morten B.], Philipsen, M.P.[Mark P.], Bahnsen, C.[Chris], Møgelmose, A.[Andreas], Moeslund, T.B.[Thomas B.], Trivedi, M.M.[Mohan M.],
Traffic Light Detection at Night: Comparison of a Learning-Based Detector and Three Model-Based Detectors,
ISVC15(I: 774-783).
Springer DOI 1601
BibRef

Wang, Y., Zhu, X.X., Zeisl, B., Pollefeys, M.,
Fusing Meter-Resolution 4-D InSAR Point Clouds and Optical Images for Semantic Urban Infrastructure Monitoring,
GeoRS(55), No. 1, January 2017, pp. 14-26.
IEEE DOI 1701
BibRef
Earlier: A1, A2, Only:
Semantic Interpretation of INSAR Estimates Using Optical Images with Application to Urban Infrastructure Monitoring,
CMRT15(153-160).
DOI Link 1602
optical images BibRef

Wang, Y., Zhu, X.X.,
Earth Observation Using SAR and Social Media Images,
EarthVision17(1580-1588)
IEEE DOI 1709
Adaptive optics, Optical imaging, Optical interferometry, Optical sensors, Solid modeling, Synthetic, aperture, radar BibRef

Zheng, H.[Han], Wang, R.S.[Rui-Sheng], Xu, S.,
Recognizing Street Lighting Poles From Mobile LiDAR Data,
GeoRS(55), No. 1, January 2017, pp. 407-420.
IEEE DOI 1701
geophysical techniques BibRef

Zheng, H.[Han], Tan, F.T.[Fei-Tong], Wang, R.S.[Rui-Sheng],
Pole-Like Object Extraction from Mobile LiDAR Data,
ISPRS16(B1: 729-734).
DOI Link 1610
BibRef

Hosseinyalamdary, S.[Siavash], Yilmaz, A.[Alper],
A Bayesian approach to traffic light detection and mapping,
PandRS(125), No. 1, 2017, pp. 184-192.
Elsevier DOI 1703
Traffic light detection and mapping BibRef

Liu, W., Li, S., Lv, J., Yu, B., Zhou, T., Yuan, H., Zhao, H.,
Real-Time Traffic Light Recognition Based on Smartphone Platforms,
CirSysVideo(27), No. 5, May 2017, pp. 1118-1131.
IEEE DOI 1705
Color, Image color analysis, Interference, Real-time systems, Roads, Smart phones, Vehicles, Finite-state machine, geometry threshold model, kernel extreme learning machine (K-ELM), smartphone, traffic, light, recognition BibRef

Wang, J.H.[Jin-Hu], Lindenbergh, R.[Roderik], Menenti, M.[Massimo],
SigVox-A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds,
PandRS(128), No. 1, 2017, pp. 111-129.
Elsevier DOI 1706
Mobile laser scanning BibRef

Zhu, H., Yuen, K.V., Mihaylova, L., Leung, H.,
Overview of Environment Perception for Intelligent Vehicles,
ITS(18), No. 10, October 2017, pp. 2584-2601.
IEEE DOI 1710
Laser radar, Roads, Intelligent vehicles, environment perception and modeling, lane and road detection, traffic sign recognition, vehicle, tracking, BibRef

Li, X., Ma, H., Wang, X., Zhang, X.,
Traffic Light Recognition for Complex Scene With Fusion Detections,
ITS(19), No. 1, January 2018, pp. 199-208.
IEEE DOI 1801
Cameras, Detectors, Feature extraction, Learning systems, Object detection, Proposals, Traffic light recognition, inter-frame analysis BibRef

Li, X., Ma, H., Wang, X.,
Region Proposal Ranking via Fusion Feature for Object Detection,
ICIP18(1298-1302)
IEEE DOI 1809
Proposals, Object detection, Feature extraction, Task analysis, Encoding, Semantics, Training, Region proposal, scoring function, object detection BibRef

Harbaš, I.[Iva], Prentašic, P.[Pavle], Subašic, M.[Marko],
Detection of roadside vegetation using Fully Convolutional Networks,
IVC(74), 2018, pp. 1-9.
Elsevier DOI 1806
Image analysis, Vegetation detection, Roadside maintenance, Deep learning, Convolutional neural networks BibRef

Krylov, V.A.[Vladimir A.], Kenny, E.[Eamonn], Dahyot, R.[Rozenn],
Automatic Discovery and Geotagging of Objects from Street View Imagery,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
To populate the data base with coordinates of fixed objects. Initially lights and poles. BibRef

de Vitry, M.M.[Matthew Moy], Schindler, K.[Konrad], Rieckermann, J.[Jörg], Leitão, J.P.[João P.],
Sewer Inlet Localization in UAV Image Clouds: Improving Performance with Multiview Detection,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
To generate an inventory. BibRef

Zadrija, V.[Valentina], Krapac, J.[Josip], Šegvic, S.[Siniša], Verbeek, J.[Jakob],
Sparse weakly supervised models for object localization in road environment,
CVIU(176-177), 2018, pp. 9-21.
Elsevier DOI 1812
BibRef
Earlier: A1, A2, A4, A3:
Patch-Level Spatial Layout for Classification and Weakly Supervised Localization,
GCPR15(492-503).
Springer DOI 1511
Object localization, Weak supervision, Fisher vectors, Sparse models, Convolutional features, OpenStreetMap BibRef

Voumard, J.[Jérémie], Derron, M.H.[Marc-Henri], Jaboyedoff, M.[Michel], Bornemann, P.[Pierrick], Malet, J.P.[Jean-Philippe],
Pros and Cons of Structure for Motion Embarked on a Vehicle to Survey Slopes along Transportation Lines Using 3D Georeferenced and Coloured Point Clouds,
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DOI Link 1812
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Song, Y.Z.[Yong-Ze], Wright, G.[Graeme], Wu, P.[Peng], Thatcher, D.[Dominique], McHugh, T.[Tom], Li, Q.D.[Qin-Dong], Li, S.J.[Shuk Jin], Wang, X.Y.[Xiang-Yu],
Segment-Based Spatial Analysis for Assessing Road Infrastructure Performance Using Monitoring Observations and Remote Sensing Data,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
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Dick, K., Charih, F., Souley Dosso, Y., Russell, L., Green, J.R.,
Systematic Street View Sampling: High Quality Annotation of Power Infrastructure in Rural Ontario,
CRV18(134-141)
IEEE DOI 1812
Google, Complexity theory, Roads, Systematics, Machine vision, Image resolution, Limiting, Sampling Methods, Remote Sensing, Open Source Software BibRef

Wang, J., Zhou, L.,
Traffic Light Recognition With High Dynamic Range Imaging and Deep Learning,
ITS(20), No. 4, April 2019, pp. 1341-1352.
IEEE DOI 1904
Image color analysis, Machine learning, Cameras, Lighting, Image recognition, Robustness, Histograms, deep learning BibRef

Lee, E.[Eunseop], Kim, D.J.[Dai-Jin],
Accurate traffic light detection using deep neural network with focal regression loss,
IVC(87), 2019, pp. 24-36.
Elsevier DOI 1906
Advanced driving assistance system, Traffic light detection, Small object detection, Deep neural network, Freestyle anchor box BibRef

Shokri, D., Rastiveis, H., Shams, A., Sarasua, W.A.,
Utility Poles Extraction From Mobile Lidar Data in Urban Area Based On Density Information,
SMPR19(1001-1007).
DOI Link 1912
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Gao, F.[Feng], Wang, C.M.[Cai-Mei],
Hybrid strategy for traffic light detection by combining classical and self-learning detectors,
IET-ITS(14), No. 7, July 2020, pp. 735-741.
DOI Link 2006
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Mao, J.[Jia], Hong, D.[Dou], Wang, X.[Xi], Hsu, C.H.[Ching-Hsien], Shanthini, A.,
CVRRSS-CHD: Computer vision-related roadside surveillance system using compound hierarchical-deep models,
IET-ITS(14), No. 11, November 2020, pp. 1353-1362.
DOI Link 2010
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Fang, L.[Lina], Shen, G.X.[Gui-Xi], Luo, H.F.[Hai-Feng], Chen, C.C.[Chong-Cheng], Zhao, Z.Y.[Zhi-Yuan],
Automatic Extraction of Roadside Traffic Facilities From Mobile Laser Scanning Point Clouds Based on Deep Belief Network,
ITS(22), No. 4, April 2021, pp. 1964-1980.
IEEE DOI 2104
Feature extraction, Machine learning, Semantics, Automobiles, Solid modeling, Biological system modeling, normalized cut
See also Individual Tree Extraction from Urban Mobile Laser Scanning Point Clouds Using Deep Pointwise Direction Embedding. BibRef

Verma, D.[Deepank], Mumm, O.[Olaf], Carlow, V.M.[Vanessa Miriam],
Identifying Streetscape Features Using VHR Imagery and Deep Learning Applications,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
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Wang, Z.Y.[Zi-Yang], Yang, L.[Lin], Sheng, Y.[Yehua], Shen, M.[Mi],
Pole-Like Objects Segmentation and Multiscale Classification-Based Fusion from Mobile Point Clouds in Road Scenes,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
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Li, G.N.[Guan-Nan], Lu, X.[Xiu], Lin, B.X.[Bing-Xian], Zhou, L.C.[Liang-Chen], Lv, G.N.[Guo-Nian],
Automatic Positioning of Street Objects Based on Self-Adaptive Constrained Line of Bearing from Street-View Images,
IJGI(11), No. 4, 2022, pp. xx-yy.
DOI Link 2205
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Tang, Q.[Quan], Liu, F.G.[Fa-Gui], Jiang, J.[Jun], Zhang, Y.[Yu],
EPRNet: Efficient Pyramid Representation Network for Real-Time Street Scene Segmentation,
ITS(23), No. 7, July 2022, pp. 7008-7016.
IEEE DOI 2207
Convolutional codes, Real-time systems, Semantics, Kernel, Encoding, Computational modeling, Image segmentation, intelligent vehicles BibRef

Yu, Y.T.[Yong-Tao], Jiang, T.[Tao], Li, Y.[Yinyin], Guan, H.Y.[Hai-Yan], Li, D.L.[Di-Long], Chen, L.H.[Liang-Hai], Yu, C.H.[Chang-Hui], Gao, L.[Li], Gao, S.B.[Shang-Bing], Li, J.[Jonathan],
SignHRNet: Street-level traffic signs recognition with an attentive semi-anchoring guided high-resolution network,
PandRS(192), 2022, pp. 142-160.
Elsevier DOI 2209
Traffic signs recognition, High-resolution network, Feature attention, Semi-anchoring, Feature alignment, Street-level image BibRef

Fang, L.[Lina], You, Z.L.[Zhi-Long], Shen, G.X.[Gui-Xi], Chen, Y.P.[Yi-Ping], Li, J.R.[Jiang-Rong],
A joint deep learning network of point clouds and multiple views for roadside object classification from lidar point clouds,
PandRS(193), 2022, pp. 115-136.
Elsevier DOI 2210
Mobile laser scanning systems, Point cloud classification, Multiview images, Deep learning, Attention mechanism BibRef

Yao, Z.[Zikai], Liu, Q.[Qiang], Xie, Q.[Qian], Li, Q.[Qing],
TL-Detector: Lightweight Based Real-Time Traffic Light Detection Model for Intelligent Vehicles,
ITS(24), No. 9, September 2023, pp. 9736-9750.
IEEE DOI 2310
BibRef

Pechinger, M.[Mathias], Schröer, G.[Guido], Bogenberger, K.[Klaus], Markgraf, C.[Carsten],
Roadside Infrastructure Support for Urban Automated Driving,
ITS(24), No. 10, October 2023, pp. 10643-10652.
IEEE DOI 2310
BibRef

Hou, Y.[Yue], Shi, H.Y.[Hong-Yu], Chen, N.[Ning], Liu, Z.[Zhuo], Wei, H.[Han], Han, Q.[Qiang],
Vision Image Monitoring on Transportation Infrastructures: A Lightweight Transfer Learning Approach,
ITS(24), No. 11, November 2023, pp. 12888-12899.
IEEE DOI 2311
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Guo, F.[Feng], Zou, F.M.[Fu-Min], Luo, S.[Sijie], Chen, H.B.[Hao-Bin], Yu, X.[Xiang], Zhang, C.[Cheng], Liao, L.[Lyuchao],
Positioning method of expressway ETC gantry by multi-source traffic data,
IET-ITS(18), No. 3, 2024, pp. 540-554.
DOI Link 2403
Electronic Toll Collection. Sensor positioning. BibRef

Wu, S.[Sean], Amenta, N.[Nicole], Zhou, J.C.[Jia-Chen], Papais, S.[Sandro], Kelly, J.[Jonathan],
aUToLights: A Robust Multi-Camera Traffic Light Detection and Tracking System,
CRV23(89-96)
IEEE DOI 2406
Filtering, Pipelines, Urban areas, Semantics, Hidden Markov models, Detectors, Vision for Autonomous Vehicles, Field Robotics, Real Time Perception BibRef

Wu, A.[Aotian], He, P.[Pan], Li, X.[Xiao], Chen, K.[Ke], Ranka, S.[Sanjay], Rangarajan, A.[Anand],
An Efficient Semi-Automated Scheme for Infrastructure LiDAR Annotation,
ITS(25), No. 7, July 2024, pp. 8237-8247.
IEEE DOI 2407
Annotations, Laser radar, Point cloud compression, Target tracking, Pedestrians, Autonomous vehicles, Point cloud annotation tool, deep learning BibRef

Yao, Z.K.[Zi-Kai], Liu, Q.[Qiang], Fu, J.[Jie], Xie, Q.[Qian], Li, B.[Bo], Ye, Q.[Qing], Li, Q.[Qing],
A Coarse-to-Fine Deep Learning Based Framework for Traffic Light Recognition,
ITS(25), No. 10, October 2024, pp. 13887-13899.
IEEE DOI 2410
Target recognition, Detectors, Image recognition, Image color analysis, Deep learning, Safety, Feature extraction, coarse-to-fine framework BibRef

Shi, H.[Hao], Pang, C.[Chengshan], Zhang, J.[JiaMing], Yang, K.L.[Kai-Lun], Wu, Y.H.[Yu-Hao], Ni, H.J.[Hua-Jian], Lin, Y.[Yining], Stiefelhagen, R.[Rainer], Wang, K.W.[Kai-Wei],
CoBEV: Elevating Roadside 3D Object Detection With Depth and Height Complementarity,
IP(33), 2024, pp. 5424-5439.
IEEE DOI 2410
Cameras, Feature extraction, Object detection, Detectors, Accuracy, Robustness, Roadside 3D object detection, autonomous driving BibRef

Yang, L.[Lei], Zhang, X.Y.[Xin-Yu], Yu, J.X.[Jia-Xin], Li, J.[Jun], Zhao, T.[Tong], Wang, L.[Li], Huang, Y.[Yi], Zhang, C.[Chuang], Wang, H.[Hong], Li, Y.M.[Yi-Ming],
MonoGAE: Roadside Monocular 3D Object Detection With Ground-Aware Embeddings,
ITS(25), No. 11, November 2024, pp. 17587-17601.
IEEE DOI 2411
Object detection, Cameras, Feature extraction, Training, Robustness, Geometry, Monocular 3D object detection, roadside perception, autonomous driving BibRef

Hao, R.Y.[Rui-Yang], Fan, S.Q.[Si-Qi], Dai, Y.[Yingru], Zhang, Z.[Zhenlin], Li, C.X.[Chen-Xi], Wang, Y.[Yuntian], Yu, H.[Haibao], Yang, W.X.[Wen-Xian], Yuan, J.[Jirui], Nie, Z.[Zaiqing],
RCooper: A Real-world Large-scale Dataset for Roadside Cooperative Perception,
CVPR24(22347-22357)
IEEE DOI Code:
WWW Link. 2410
Point cloud compression, Codes, Benchmark testing, Sensor systems, Sensors, Autonomous vehicles, dataset and benchmark BibRef

Taiana, M.[Matteo], Toso, M.[Matteo], James, S.[Stuart], del Bue, A.[Alessio],
PoserNet: Refining Relative Camera Poses Exploiting Object Detections,
ECCV22(XXXIII:247-263).
Springer DOI 2211
BibRef

Ahmad, J.[Javed], Toso, M.[Matteo], Taiana, M.[Matteo], James, S.[Stuart], del Bue, A.[Alessio],
Multi-view 3D Objects Localization from Street-Level Scenes,
CIAP22(II:89-101).
Springer DOI 2205
BibRef

Waltner, G.[Georg], Jaschik, M.[Malte], Rinnhofer, A.[Alfred], Possegger, H.[Horst], Bischof, H.[Horst],
An Intelligent Scanning Vehicle for Waste Collection Monitoring,
CIAP22(I:38-50).
Springer DOI 2205
BibRef

Omar, W., Lee, I., Lee, G., Park, K.M.,
Detection and Localization of Traffic Lights Using Yolov3 and Stereo Vision,
ISPRS20(B2:1247-1252).
DOI Link 2012
BibRef

Matsumoto, H., Mori, Y., Masuda, H.,
Extraction and Shape Reconstruction of Guardrails Using Mobile Mapping Data,
Laser19(1061-1068).
DOI Link 1912
BibRef

Chen, Y.H.[Yu-Hua], Li, W.[Wen], Van Gool, L.J.[Luc J.],
ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes,
CVPR18(7892-7901)
IEEE DOI 1812
Semantics, Image segmentation, Adaptation models, Task analysis, Data models, Computational modeling, Feature extraction BibRef

Rad, M.S.[Mohammad Saeed], von Kaenel, A.[Andreas], Droux, A.[Andre], Tieche, F.[Francois], Ouerhani, N.[Nabil], Ekenel, H.K.[Hazim Kemal], Thiran, J.P.[Jean-Philippe],
A Computer Vision System to Localize and Classify Wastes on the Streets,
CVS17(195-204).
Springer DOI 1711
BibRef

Zhou, C., Yang, J., Zhao, C., Hua, G.,
Fast, Accurate Thin-Structure Obstacle Detection for Autonomous Mobile Robots,
ECVW17(318-327)
IEEE DOI 1709
Cameras, Feature extraction, Image edge detection, Simultaneous localization and mapping. BibRef

Hebbalaguppe, R., Garg, G., Hassan, E., Ghosh, H., Verma, A.,
Telecom Inventory Management via Object Recognition and Localisation on Google Street View Images,
WACV17(725-733)
IEEE DOI 1609
Google, Inventory management, Object recognition, Pipelines, Support vector machines, Telecommunications BibRef

Chacra, D.B.A.[David B. Abou], Zelek, J.S.[John S.],
Fully Automated Road Defect Detection Using Street View Images,
CRV17(353-360)
IEEE DOI 1804
BibRef
And:
Road Segmentation in Street View Images Using Texture Information,
CRV16(424-431)
IEEE DOI 1612
civil engineering computing, condition monitoring, crack detection, feature extraction, image classification, Road Segmentation. Fisher Vectors BibRef

Dhiman, V.[Vikas], Tran, Q.H.[Quoc-Huy], Corso, J.J.[Jason J.], Chandraker, M.[Manmohan],
A Continuous Occlusion Model for Road Scene Understanding,
CVPR16(4331-4339)
IEEE DOI 1612
BibRef

Naharudin, N., Ahamad, M.S.S., Sadullah, A.F.M.,
GIS Data Collection for Pedestrian Facilities and Furniture Using MAPINR for Android,
GGT16(89-95).
DOI Link 1612
BibRef

Moorfield, B.[Bradley], Haeusler, R.[Ralf], Klette, R.[Reinhard],
Bilateral Filtering of 3D Point Clouds for Refined 3D Roadside Reconstructions,
CAIP15(II:394-402).
Springer DOI 1511
BibRef

Haltakov, V.[Vladimir], Mayr, J.[Jakob], Unger, C.[Christian], Ilic, S.[Slobodan],
Semantic Segmentation Based Traffic Light Detection at Day and at Night,
GCPR15(446-457).
Springer DOI 1511
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Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Railroads, Inspection, Obstacles .