Survey of Pedestrian Detection for Advanced Driver Assistance Systems

By David Gerónimo Gómez, Antonio M. López, Angel Domingo Sappa, Thorsten Graf. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010

1,064 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/451c3bea362a95e59673584b35818d426c8104f5

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In Automotive Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Data-Driven Intelligent Transportation Systems: A Survey (2011, background): “For a more comprehensive review of research on pedestrian detection and protection, see [38], [42], and [43].”
Optimized Pedestrian Detection for Multiple and Occluded People (2013, neutral): “Since sliding window methods usually generate multiple overlapping detections on a person, the common final step is to apply non-maximum suppression as an attempt to remove false positive detections [9, 11].”
A survey of appearance models in visual object tracking (2013, neutral): “Table I. Summary of Related Literature Surveys Authors Topic Journal/conference title [Gerónimo et al. 2010] Pedestrian Detection IEEE Trans.”
Human detection from images and videos: A survey (2016, background): “A review of the literature on human detection problem indicates that the various proposed solutions have been either based on studies of human motion analysis (see for example, [162, 104, 105, 3, 45]) or pedestrian detection in the context of driving assistance systems (see for example, [41, 42, 78,”
Towards Large-Scale Small Object Detection: Survey and Benchmarks (2022, background): “task such as pedestrian detection [15], [16], [17], text detection [18], detection in remote sensing images [19], [20], and detection under traffic scenarios [21], [22], etc.”
Pedestrian Detection: An Evaluation of the State of the Art (2012, methodology): “mance is a lower bound for the performance of a full system and that tracking, contextual information, and the use of additional sensors can help reduce false alarms and improve detection rates (see [2]).”
Exploring Weak Stabilization for Motion Feature Extraction (2013, background): “1063-6919/13 $26.00 © 2013 IEEE DOI 10.1109/CVPR.2013.371 28802 In this paper, we posit (and verify by experiment) that the majority of useful motion information for detecting articulated objects such as people is contained in part-centric motion.”
Autonomous braking system via deep reinforcement learning (2017, background): “Recently, several safety systems including collision avoidance, pedestrian detection, and front collision warning (FCW) have been proposed to enhance the safety of the autonomous vehicle [1]–[4].”
A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles (2016, neutral): “CONTENTS I Introduction 2”
A Multilevel Mixture-of-Experts Framework for Pedestrian Classification (2011, methodology): “See [10], [16], [ 20 ], and [23] for recent surveys and performance studies.”
Robust Multi-resolution Pedestrian Detection in Traffic Scenes (2013, background): “We refer the detailed surveys on pedestrian detection to [21, 14].”
Video-Based Human Behavior Understanding: A Survey (2013, background): “Recent reviews on human behavior understanding focused on specific aspects of the overall problem, such as monocular pedestrian detection [11], human detection for driver-assistance systems [12], and pedestrian detection benchmarks [13], [14].”