Keywords
Artificial intelligenceComputer scienceFace detectionAdaBoostPattern recognition (psychology)Object-class detectionClassifier (UML)Computer visionDetectorFace (sociological concept)Facial recognition systemViola–Jones object detection frameworkComputationAlgorithm
Affiliated Institutions
Related Publications
A general framework for object detection
This paper presents a general trainable framework for object detection in static images of cluttered scenes. The detection technique we develop is based on a wavelet representat...
Rapid object detection using a boosted cascade of simple features
This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This wor...
A Deep Sum-Product Architecture for Robust Facial Attributes Analysis
Recent works have shown that facial attributes are useful in a number of applications such as face recognition and retrieval. However, estimating attributes in images with large...
Local Features and Kernels for Classification of Texture and Object Categories: An In-Depth Study
Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that rep...
Learning SURF Cascade for Fast and Accurate Object Detection
This paper presents a novel learning framework for training boosting cascade based object detector from large scale dataset. The framework is derived from the well-known Viola-J...
Publication Info
- Year
- 2004
- Type
- article
- Volume
- 57
- Issue
- 2
- Pages
- 137-154
- Citations
- 14078
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
14078
OpenAlex
Cite This
Paul Viola,
Michael Jones
(2004).
Robust Real-Time Face Detection.
International Journal of Computer Vision
, 57
(2)
, 137-154.
https://doi.org/10.1023/b:visi.0000013087.49260.fb
Identifiers
- DOI
- 10.1023/b:visi.0000013087.49260.fb