On-road vehicle detection: a review

By Zehang Sun, George Bebis, Ronald Miller. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006

1,265 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/6c8d8a2df11b4df22857a1b48a8a607ed3811d67

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Vehicle Detection Using Normalized Color and Edge Map (2007, background): “Index Terms—Edge maps, intelligent transportation system, normalized color, vehicle detection.”
A Review of Computer Vision Techniques for the Analysis of Urban Traffic (2011, background): “tance and autonomous driving can be found in [130].”
Understanding Transit Scenes: A Survey on Human Behavior-Recognition Algorithms (2010, neutral): “detection systems, see [152].”
Research Advances and Challenges of Autonomous and Connected Ground Vehicles (2019, neutral): “It is mainly utilized for vehicle [37], [104], pedestrian [105]– [107], lane marking [108]– [110] and trafﬁc sign [111] detection in AV.”
Self-sensing piezoresistive cement composite loaded with carbon black particles (2017, background): “Roadways management and logistics have also benefitd from SHM [3].”
Survey of Pedestrian Detection for Advanced Driver Assistance Systems (2010, methodology): “For instance, in Sun's vehicle detection review [13], techniques are divided into hypothesis generation and hypothesis validation, thus allowing the reader to concentrate on the methods for solving simpler problems, rather than approaching the problem as a whole.”
Framework for Performance Evaluation of Face, Text, and Vehicle Detection and Tracking in Video: Data, Metrics, and Protocol (2009, neutral): “[50] presented a review of vision-based on-road vehicle detection systems where the camera is mounted on the vehicle.”
Data-Driven Intelligent Transportation Systems: A Survey (2011, background): “following five main issues are listed as follows [35].”
Multiple object tracking: A literature review (2014, background): “f targets, such as pedestrians, vehicles or faces. The reason behind is that detection of these objects has gained great progress in the recent years [Dalal and Triggs 2005; Felzenszwalb et al. 2010; Sun et al. 2006]. Third, the performance of ABT approaches depends on the performance of the employe”
Vehicle Detection Techniques for Collision Avoidance Systems: A Review (2015, methodology): “It is also recommend to read other comprehensive reviews [12] and [13] for driver safety systems.”
A Survey on Performance Metrics for Object-Detection Algorithms (2020, methodology): “The Viola-Jones framework [2], for instance, became popular due to its successful application in the face-detection problem [3], and was later applied to different subtasks such as pedestrian [4] and car [5] detections.”