17.1.3.2.13 Crosswalk Detection, Zebra Crossings

Chapter Contents (Back)
Zebra Crossings. Crosswalks. Pedestrian.
See also Pedestrian Safety Issues, Pedestrian Behavior.

Uddin, M.S., Shioyama, T.,
Detection of Pedestrian Crossing Using Bipolarity Feature: An Image-Based Technique,
ITS(6), No. 4, December 2005, pp. 439-445.
IEEE DOI 0601
BibRef

Shioyama, T., Wu, H.Y.[Hai-Yuan], Nishibe, Y., Nakamura, N., Kitawaki, S.,
Image analysis of crosswalk,
CIAP01(168-173).
IEEE DOI 0210
BibRef

Jiang, X., Wang, W., Bengler, K.,
Intercultural Analyses of Time-to-Collision in Vehicle-Pedestrian Conflict on an Urban Midblock Crosswalk,
ITS(16), No. 2, April 2015, pp. 1048-1053.
IEEE DOI 1504
Accidents BibRef

Li, L.[Lin], Zhang, D.[Da], Ying, S.[Shen], Li, Y.[You],
Recognition and Reconstruction of Zebra Crossings on Roads from Mobile Laser Scanning Data,
IJGI(5), No. 7, 2016, pp. 125.
DOI Link 1608
BibRef

Mascetti, S.[Sergio], Ahmetovic, D.[Dragan], Gerino, A.[Andrea], Bernareggi, C.[Cristian],
ZebraRecognizer: Pedestrian crossing recognition for people with visual impairment or blindness,
PR(60), No. 1, 2016, pp. 405-419.
Elsevier DOI 1609
BibRef
Earlier: A2, A4, A3, A1:
ZebraRecognizer: Efficient and Precise Localization of Pedestrian Crossings,
ICPR14(2566-2571)
IEEE DOI 1412
Accelerometers Visual impairment
See also Robust traffic lights detection on mobile devices for pedestrians with visual impairment. BibRef

Sun, Y.B.[Yan-Biao], Zhang, F.[Fan], Gao, Y.L.[Yun-Long], Huang, X.F.[Xian-Feng],
Extraction and Reconstruction of Zebra Crossings from High Resolution Aerial Images,
IJGI(5), No. 8, 2016, pp. 127.
DOI Link 1609
BibRef

Córdoba, A., Astrain, J.J., Villadangos, J., Azpilicueta, L., López-Iturri, P., Aguirre, E., Falcone, F.,
SesToCross: Semantic Expert System to Manage Single-Lane Road Crossing,
ITS(18), No. 5, May 2017, pp. 1221-1233.
IEEE DOI 1705
Automobiles, Ontologies, Real-time systems, Roads, Semantics, Sensors, Advanced driver assistance system, anticipation, crossroads, ontology, real-time decision making, safety, traffic, management BibRef

Jiang, X.B.[Xiao-Bei], Wang, W.H.[Wu-Hong], Bengler, K.[Klaus], Guo, H.W.[Hong-Wei], Li, C.G.[Cheng-Gang],
Analysis of drivers' performance in response to potential collision with pedestrians at urban crosswalks,
IET-ITS(11), No. 9, November 2017, pp. 546-552.
DOI Link 1710
BibRef

Völz, B., Mielenz, H., Gilitschenski, I., Siegwart, R., Nieto, J.,
Inferring Pedestrian Motions at Urban Crosswalks,
ITS(20), No. 2, February 2019, pp. 544-555.
IEEE DOI 1902
Trajectory, Prediction algorithms, Automobiles, Roads, Safety, Measurement, Task analysis, Autonomous vehicles, machine learning, prediction methods BibRef

Chen, A.T., Fan, J., Biglari-Abhari, M., Wang, K.I.,
A computationally efficient pipeline for camera-based indoor person tracking,
IVCNZ17(1-6)
IEEE DOI 1902
feature extraction, image matching, object detection, target tracking, unsupervised learning, video cameras, Camera Surveillance BibRef

Cao, Z.C.[Zheng-Cai], Xu, X.W.[Xiao-Wen], Hu, B.[Biao], Zhou, M.C.[Meng-Chu],
Rapid Detection of Blind Roads and Crosswalks by Using a Lightweight Semantic Segmentation Network,
ITS(22), No. 10, October 2021, pp. 6188-6197.
IEEE DOI 2110
Convolution, Roads, Semantics, Feature extraction, Image segmentation, Kernel, Machine learning, deep convolutional network BibRef

Cadena, P.R.G.[Pablo Rodrigo Gantier], Qian, Y.Q.[Ye-Qiang], Wang, C.X.[Chun-Xiang], Yang, M.[Ming],
Pedestrian Graph+: A Fast Pedestrian Crossing Prediction Model Based on Graph Convolutional Networks,
ITS(23), No. 11, November 2022, pp. 21050-21061.
IEEE DOI 2212
Predictive models, Data models, Computational modeling, Pose estimation, Task analysis, Real-time systems, Convolution, graph convolutional network BibRef

Ni, R.R.[Rong-Rong], Yang, B.[Biao], Wei, Z.W.[Zhi-Wen], Hu, H.Y.[Hong-Yu], Yang, C.C.[Chang-Chun],
Pedestrians crossing intention anticipation based on dual-channel action recognition and hierarchical environmental context,
IET-ITS(17), No. 2, 2023, pp. 255-269.
DOI Link 2302
BibRef

Zhou, Y.C.[Yu-Chen], Tan, G.[Guang], Zhong, R.[Rui], Li, Y.[Yaokun], Gou, C.[Chao],
PIT: Progressive Interaction Transformer for Pedestrian Crossing Intention Prediction,
ITS(24), No. 12, December 2023, pp. 14213-14225.
IEEE DOI 2312
BibRef


Liu, H.Z.[Han-Zhou], Lu, M.[Mi],
A Crosswalk Stripe Detection Model Based on Gradient Similarity Tags,
ICIVC22(114-122)
IEEE DOI 2301
Deep learning, Shape, Computational modeling, Roads, Neural networks, Lighting, Detectors, Intelligent driving systems, Similarity coefficient BibRef

Xu, R.S.[Run-Sheng], Tafazzoli, F.[Faezeh], Zhang, L.[Li], Rehfeld, T.[Timo], Krehl, G.[Gunther], Seal, A.[Arunava],
Holistic Grid Fusion Based Stop Line Estimation,
ICPR21(8400-8407)
IEEE DOI 2105
Visualization, Roads, Sensor fusion, Sensor phenomena and characterization, Feature extraction, Online map validation BibRef

Yu, S.[Samuel], Lee, H.[Heon], Kim, J.[John],
LYTNet: A Convolutional Neural Network for Real-Time Pedestrian Traffic Lights and Zebra Crossing Recognition for the Visually Impaired,
CAIP19(I:259-270).
Springer DOI 1909
BibRef

Liang, J.[Justin], Urtasun, R.[Raquel],
End-to-End Deep Structured Models for Drawing Crosswalks,
ECCV18(XII: 407-423).
Springer DOI 1810
BibRef

Diaz, M., Girgis, R., Fevens, T., Cooperstock, J.,
To Veer or Not to Veer: Learning from Experts How to Stay Within the Crosswalk,
ACVR17(1470-1479)
IEEE DOI 1802
Cameras, Gyroscopes, Mobile handsets, Sensors, Training, Urban areas BibRef

Rasouli, A., Kotseruba, I., Tsotsos, J.K.,
Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior,
CVRoads17(206-213)
IEEE DOI 1802
Automobiles, Cameras, Meteorology, Roads, Trajectory, Videos BibRef

Tosi, F.[Fabio], Poggi, M.[Matteo], Benincasa, A.[Antonio], Mattoccia, S.[Stefano],
Beyond Local Reasoning for Stereo Confidence Estimation with Deep Learning,
ECCV18(VI: 323-338).
Springer DOI 1810
BibRef

Perry, A.[Adi], Verbin, D.[Dor], Kiryati, N.[Nahum],
Crossing the Road Without Traffic Lights: An Android-Based Safety Device,
CIAP17(II:534-544).
Springer DOI 1711
pedestrian safety. BibRef

Perry, A.[Adi], Kiryati, N.[Nahum],
Road-Crossing Assistance by Traffic Flow Analysis,
ACVR14(361-374).
Springer DOI 1504
BibRef

Poggi, M.[Matteo], Mattoccia, S.[Stefano],
Deep Stereo Fusion: Combining Multiple Disparity Hypotheses with Deep-Learning,
3DV16(138-147)
IEEE DOI 1701
convolution BibRef

Poggi, M.[Matteo], Nanni, L.[Luca], Mattoccia, S.[Stefano],
Crosswalk Recognition Through Point-Cloud Processing and Deep-Learning Suited to a Wearable Mobility Aid for the Visually Impaired,
ISCA15(282-289).
Springer DOI 1511
BibRef

Arias, P., Riveiro, B., Soilán, M., Díaz-Vilariño, L., Martínez-Sánchez, J.,
Simple Approaches to Improve the Automatic Inventory of Zebra Crossing from MLS Data,
CMRT15(103-108).
DOI Link 1602
BibRef

Gavrilovic, T.[Thomas], Ninot, J.[Jérôme], Smadja, L.[Laurent],
Frequency filtering and connected components characterization for zebra-crossing and hatched markings detection,
PCVIA10(A:43).
PDF File. 1009
BibRef

Zhao, Q., Zhang, G.Y., Wood, R.L., Luo, Z.W.,
Video Based Real-Time Pedestrian Detection on Zebra Cross,
CISP09(1-4).
IEEE DOI 0910
BibRef

Soheilian, B., Paparoditis, N., Boldo, D., Rudant, J.P.,
3D zebra-crossing reconstruction from stereo rig images of a ground-based mobile mapping system,
IEVM06(xx-yy).
PDF File. 0609
BibRef

Uddin, M.S., Shioyama, T.[Tadayoshi],
Bipolarity and Projective Invariant-Based Zebra-Crossing Detection for the Visually Impaired,
VisImpaired05(III: 22-22).
IEEE DOI 0507
projective invarients to recognize crossing from candidates. BibRef

Se, S.[Stephen],
Zebra-Crossing Detection for the Partially Sighted,
CVPR00(II: 211-217).
IEEE DOI 0005
Crosswalks BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Pedestrian Safety Issues, Pedestrian Behavior .


Last update:Mar 16, 2024 at 20:36:19