Face recognition using SURF features

Du, Geng; Su, Fei; Cai, Anni

doi:10.1117/12.832636

Cited by 78 publications

(35 citation statements)

References 11 publications

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“…In the detection phase, important points of interest are found on the image. In order to find these points of interest, blob-like structures are located where the determinant is at maximum (Du, 2009). The description phase describes the features using Haar Wavelets.…”

Section: Speed-up Robust Feature (Surf)mentioning

confidence: 99%

Design and Implementation of a Hybrid Face Recognition Technique

Chaudhry

Elgazzar

2019

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)

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Section: Speed-up Robust Feature (Surf)mentioning

confidence: 99%

Design and Implementation of a Hybrid Face Recognition Technique

Chaudhry

Elgazzar

2019

2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC)

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“…They extracted interest points from images in combination with the bag-of-words method to obtain adequate retrieval and classification results. In [22,23], the authors used SURF detectors and descriptors for facial recognition. The keypoints were extracted from facial images following image processing procedures, such as histogram equalization and normalization.…”

Section: Research Backgroundmentioning

confidence: 99%

Artwork Identification for 360-Degree Panoramic Images Using Polyhedron-Based Rectilinear Projection and Keypoint Shapes

Jin

Kim

2017

Applied Sciences

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Abstract:With the increased development of 360-degree production technologies, artwork has recently been photographed without authorization. To prevent this infringement, we propose an artwork identification methodology for 360-degree images. We transform the 360-degree image into a three-dimensional sphere and wrap it with a polyhedron. On the sphere, several points are located on the polyhedron to determine the width, height, and direction of the rectilinear projection. The 360-degree image is divided and transformed into several rectilinear projected images to reduce the adverse effects from the distorted panoramic image. We also propose a method for improving the identification precision of artwork located at a highly distorted position using the difference of keypoint shapes. After applying the proposed methods, identification precision is increased by 45% for artwork that is displayed on a 79-inch monitor in a seriously distorted position with features that were generated by scale-invariant feature transformations.

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“…Rather than dividing the image into fixed subregions, Du et al propose in [6] a sliding window approach in combination with SURF descriptors. Only template features lying within a specified search window around the image position of the currently inspected test feature are considered for matching.…”

Section: B Face Identificationmentioning

confidence: 99%

A new method for combined face detection and identification using interest point descriptors

Stein

Fink

2011

Face and Gesture 2011

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Abstract-Although face recognition has been an active research area for decades, the general problem is still unsolved. While many methods addressing either face detection or face identification emerged, little attention has been paid to the combination or integration of detection and identification.In this paper we propose a combined method for face detection and identification using SIFT descriptors. This combined method includes an existing detection model and a new identification method based on object class invariants (OCIs), which is invariant to translation, scale, in-plane rotation and small 3D viewpoint changes. These models are combined using a bounding box around the OCI to filter face features for identification. We show the highly competitive performance of the newly developed identification method and the effectiveness of the proposed combination scheme.

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Face recognition using SURF features

Cited by 78 publications

References 11 publications

Design and Implementation of a Hybrid Face Recognition Technique

Design and Implementation of a Hybrid Face Recognition Technique

Artwork Identification for 360-Degree Panoramic Images Using Polyhedron-Based Rectilinear Projection and Keypoint Shapes

A new method for combined face detection and identification using interest point descriptors

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