As the current binary descriptors have disadvantages of high computational complexity, no affine invariance, and the high false matching rate with viewpoint changes, a new binary affine invariant descriptor, called BAND, is proposed. Different from other descriptors, BAND has an irregular pattern, which is based on local affine invariant region surrounding a feature point, and it has five orientations, which are obtained by LBP effectively. Ultimately, a 256 bits binary string is computed by simple random sampling pattern. Experimental results demonstrate that BAND has a good matching result in the conditions of rotating, image zooming, noising, lighting, and small-scale perspective transformation. It has better matching performance compare...
Image matching is a fundamental step in several computer vision applications where the requirement i...
In this paper, we introduce a local image descriptor that is inspired by earlier detectors such as S...
Abstract. Most descriptor-based keypoint recognition methods require computationally expensive patch...
Image matching has a vital role in many of the present day computer vision applications such as trac...
A very simple but efficient feature descriptor is proposed for image matching/registration applicati...
The traditional scale invariant feature transform (SIFT) method can extract distinctive features for...
Abstract — The efficiency and quality of a feature descriptor are critical to the user experience of...
International audienceThe classic approach to image matching consists in the detection , description...
Fast and robust feature extraction is crucial for many computer vision applications such as image ma...
In this paper, an orientation and scale invariant binary descriptor is proposed, which can be used i...
International audienceThis paper proposes a new version of LBP and its inclusion into covariance reg...
An affine invariant descriptor is proposed, which is able to well represent the affine covariant reg...
International audienceWe are addressing the problem of matching images of scene or of objects when a...
International audienceWe are addressing the problem of matching images of scene or of objects when a...
Abstract. Local feature descriptors are widely used in many computer vision applications. Over the p...
Image matching is a fundamental step in several computer vision applications where the requirement i...
In this paper, we introduce a local image descriptor that is inspired by earlier detectors such as S...
Abstract. Most descriptor-based keypoint recognition methods require computationally expensive patch...
Image matching has a vital role in many of the present day computer vision applications such as trac...
A very simple but efficient feature descriptor is proposed for image matching/registration applicati...
The traditional scale invariant feature transform (SIFT) method can extract distinctive features for...
Abstract — The efficiency and quality of a feature descriptor are critical to the user experience of...
International audienceThe classic approach to image matching consists in the detection , description...
Fast and robust feature extraction is crucial for many computer vision applications such as image ma...
In this paper, an orientation and scale invariant binary descriptor is proposed, which can be used i...
International audienceThis paper proposes a new version of LBP and its inclusion into covariance reg...
An affine invariant descriptor is proposed, which is able to well represent the affine covariant reg...
International audienceWe are addressing the problem of matching images of scene or of objects when a...
International audienceWe are addressing the problem of matching images of scene or of objects when a...
Abstract. Local feature descriptors are widely used in many computer vision applications. Over the p...
Image matching is a fundamental step in several computer vision applications where the requirement i...
In this paper, we introduce a local image descriptor that is inspired by earlier detectors such as S...
Abstract. Most descriptor-based keypoint recognition methods require computationally expensive patch...