Pedestrian Detection: An Evaluation of the State of the Art

Pedestrian detection is a key problem in computer vision, with several applications that have the potential to positively impact quality of life. In recent years, the number of approaches to detecting pedestrians in monocular images has grown steadily. However, multiple data sets and widely varying...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 34; H. 4; S. 743 - 761
Hauptverfasser:	Dollar, P., Wojek, C., Schiele, B., Perona, P.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Los Alamitos, CA IEEE 01.04.2012 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Applied sciences Artificial intelligence Automatic Data Processing benchmark Caltech Pedestrian data set Cameras Computer science; control theory; systems Detectors evaluation Exact sciences and technology Heating Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Labeling object detection Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Pedestrian detection Pixel Sensitivity and Specificity Studies Testing Training Performance evaluation Occlusion Caltech Pedestrian data set Computer vision Statistical analysis Image processing data set Pedestrian Monocular vision Low resolution Pedestrian detection Object recognition Annotation benchmark Quality of life evaluation Object detection Occultation
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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