{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T15:29:41Z","timestamp":1778081381196,"version":"3.51.4"},"reference-count":35,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2011,9,21]],"date-time":"2011-09-21T00:00:00Z","timestamp":1316563200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a systematic scheme for fusing millimeter wave (MMW) radar and a monocular vision sensor for on-road obstacle detection. As a whole, a three-level fusion strategy based on visual attention mechanism and driver\u2019s visual consciousness is provided for MMW radar and monocular vision fusion so as to obtain better comprehensive performance. Then an experimental method for radar-vision point alignment for easy operation with no reflection intensity of radar and special tool requirements is put forward. Furthermore, a region searching approach for potential target detection is derived in order to decrease the image processing time. An adaptive thresholding algorithm based on a new understanding of shadows in the image is adopted for obstacle detection, and edge detection is used to assist in determining the boundary of obstacles. The proposed fusion approach is verified through real experimental examples of on-road vehicle\/pedestrian detection. In the end, the experimental results show that the proposed method is simple and feasible.<\/jats:p>","DOI":"10.3390\/s110908992","type":"journal-article","created":{"date-parts":[[2011,9,22]],"date-time":"2011-09-22T09:52:40Z","timestamp":1316685160000},"page":"8992-9008","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":121,"title":["Integrating Millimeter Wave Radar with a Monocular Vision Sensor for On-Road Obstacle Detection Applications"],"prefix":"10.3390","volume":"11","author":[{"given":"Tao","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nanning","family":"Zheng","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingmin","family":"Xin","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Ma","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2011,9,21]]},"reference":[{"key":"ref_1","unstructured":"Jones, TO, Grimes, DM, Dork, RA, and Regueiro, WR (1973, January 11\u201314). Automotive Radar-Problems and Promises (Tech. Paper). San Francisco, CA, USA."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1109\/PROC.1974.9520","article-title":"Automotive Radar: A Brief Review","volume":"62","author":"Grimes","year":"1974","journal-title":"Proc. IEEE"},{"key":"ref_3","first-page":"49","article-title":"Automotive station keeping and braking radars: A review","volume":"18","author":"Jones","year":"1975","journal-title":"Microwave J"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1109\/25.45465","article-title":"Cradar- an open-loop extended-mono pulse automotive radar","volume":"38","author":"Grimes","year":"1989","journal-title":"IEEE Trans. Vehicular Technol"},{"key":"ref_5","unstructured":"Kimoto, K, and Thorpe, C (1997, January 7\u201311). Map Building with Radar and Motion Sensors for Automated Highway Vehicle Navigation. Grenoble, France."},{"key":"ref_6","unstructured":"Clark, S (2002). Autonomous Land Vehicle Navigation Using Millimeter Wave Radar, Ph.D. thesis,."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1016\/j.robot.2009.02.001","article-title":"Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles","volume":"57","author":"Kendoul","year":"2009","journal-title":"Robot. Auton. Syst"},{"key":"ref_8","first-page":"1179","article-title":"Real-time tacking and indentification of moving persons by using a camera in outdoor environment","volume":"5","author":"Sugandi","year":"2009","journal-title":"Int. J. Innov. Comput. Inf. Control"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Schulz, H-W, Buschmann, M, Kruger, L, and Winkler, S Vision-Based Autonomous Landing for Small UAVs-First Experimental Results. AIAA, 2005\u20136980.","DOI":"10.2514\/6.2005-6980"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Santosh, D, Achar, S, and Jawahar, CV (2008, January 19\u201323). Autonomous Image-Based Exploration for Mobile Robot Navigation. Pasadena, CA, USA.","DOI":"10.1109\/ROBOT.2008.4543622"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Park, S, Kim, E, Lee, H, and Jung, H (2008, January 14\u201317). Multiple Data Association and Tracking Using Millimeter Wave Radar. Seoul, Korea.","DOI":"10.1109\/ICCAS.2008.4694467"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1109\/TITS.2006.888597","article-title":"Vehicle and guard rail detection using radar and vision data fusion","volume":"8","author":"Alessandretti","year":"2007","journal-title":"IEEE Trans. Intell. Transp. Syst"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1109\/TITS.2009.2032769","article-title":"Collision Sensing by Stereo Vision and Radar Sensor Fusion","volume":"10","author":"Wu","year":"2009","journal-title":"IEEE Trans. Intell. Transp. Syst"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1109\/TITS.2002.802926","article-title":"Depth-based target segmentation for intelligent vehicles: Fusion of radar and binocular stereo","volume":"13","author":"Fang","year":"2002","journal-title":"IEEE Trans. Intell. Transp. Syst"},{"key":"ref_15","unstructured":"Bauson, WA Available online: http:\/\/www.sae.org\/events\/gim\/presentations\/2010\/williambauson.pdf (accessed on 19 September 2011)."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sugimoto, S, Tateda, H, Takahashi, H, and Okutomi, M (2004, January 23\u201326). Obstacle Detection Using Millimeter-Wave Radar and Its Visualization on Image Sequence. Cambridge, UK.","DOI":"10.1109\/ICPR.2004.1334537"},{"key":"ref_17","first-page":"55","article-title":"Moving obstacle segmentation using MMW radar and image sequence","volume":"2","author":"Sugimoto","year":"2004","journal-title":"Int. J. ITS Res"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Bertozzi, M, Bombini, L, Cerri, P, Medici, P, Antonello, PC, and Miglietta, M (2008, January 4\u20136). Obstacle Detection and Classification Fusing Radar and Vision. Eindhoven, The Netherlands.","DOI":"10.1109\/IVS.2008.4621304"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, T, Zheng, N, and Mei, K (2009, January 17\u201318). A Visual Brain Chip Based on Selective Attention for Robot Vision Application. Pasadena, CA, USA.","DOI":"10.1109\/SMC-IT.2009.19"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1038\/35058500","article-title":"Computational modeling of visual attention","volume":"2","author":"Itti","year":"2001","journal-title":"Nat. Rev. Neurosci"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1109\/TPAMI.2006.104","article-title":"On road vehicle detection: A review","volume":"28","author":"Sun","year":"2006","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1109\/TPAMI.2009.122","article-title":"Survey of pedestrian detection for advanced driver assistance systems","volume":"32","author":"Geronimo","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"ref_23","first-page":"1179","article-title":"Real time tracking and identification of moving persons by using a camera in outdoor environment","volume":"5","author":"Sugandi","year":"2009","journal-title":"Int. J. Innov. Comput. Inf. Control"},{"key":"ref_24","unstructured":"Lu, J, Yang, M, Wang, H, and Zhang, B (2002, January 19\u201325). Vision-Based Real-Time Road Detection in Urban Traffic. San Jose, CA, USA."},{"key":"ref_25","unstructured":"Zhang, W, and Sadekar, V Road-Edge Detection, US Patent US2010\/0017060, 21 January 2010."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Routray, A, and Mohanty, KB (2007, January 17\u201320). A Fast Edge Detection Algorithm for Road Boundary Extraction Under Non-uniform Light Condition. Rourkela, India.","DOI":"10.1109\/ICIT.2007.9"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1049\/el:20080608","article-title":"Ant colony optimization algorithm for detection and tracking of non-structured roads","volume":"44","author":"Arnay","year":"2008","journal-title":"Electron. Lett"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1109\/TITS.2008.2006733","article-title":"Robust road modeling and tracking using condensation","volume":"9","author":"Wang","year":"2008","journal-title":"IEEE Trans. Intell. Tran. Syst"},{"key":"ref_29","first-page":"285","article-title":"A threshold selection method from gray-level histograms","volume":"11","author":"Otsu","year":"1975","journal-title":"Automatica"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2516","DOI":"10.1016\/j.sigpro.2007.04.001","article-title":"Image histogram thresholding based on multi-objective optimization","volume":"87","author":"Nakib","year":"2007","journal-title":"Signal Proc"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1644","DOI":"10.1016\/j.patrec.2006.03.009","article-title":"Automatic thresholding for defect detection","volume":"27","author":"Ng","year":"2006","journal-title":"Pattern Recognit. Lett"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Janesick, JR (2001). Scientific Charge-Coupled Devices, SPIE Express.","DOI":"10.1117\/3.374903"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"986","DOI":"10.1109\/T-ED.1971.17320","article-title":"Charge-coupled imaging devices: Design considerations","volume":"18","author":"Amelio","year":"1971","journal-title":"IEEE Trans. Electron. Devices"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1104\/pp.47.5.656","article-title":"Reflectance and Transmittance of Light by Leaves","volume":"47","author":"Wooley","year":"1971","journal-title":"Plant Physiol"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Wang, T, Xin, J, and Zheng, N (2011, January 2\u20134). A Method Integrating Human Visual Attention and Consciousness of Radar and Vision Fusion for Autonomous Vehicle Navigation. Palo Alto, CA, USA.","DOI":"10.1109\/SMC-IT.2011.15"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/11\/9\/8992\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:57:27Z","timestamp":1760219847000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/11\/9\/8992"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,9,21]]},"references-count":35,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2011,9]]}},"alternative-id":["s110908992"],"URL":"https:\/\/doi.org\/10.3390\/s110908992","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,9,21]]}}}