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Geodesic Invariant Feature: A Local Descriptor in Depth
IEEE Transactions on Image Processing, 2015Different from the photometric images, depth images resolve the distance ambiguity of the scene, while the properties, such as weak texture, high noise, and low resolution, may limit the representation ability of the well-developed descriptors, which are elaborately designed for the photometric images.
Yazhou Liu +3 more
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A local feature descriptor based on Local Binary Patterns
2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2016This paper presents a local feature descriptor based on Local Binary Patterns (LBP). This descriptor uses binary bit string to represent the local region of images and the integral image to mean filter that makes descriptor building faster. Compared to Scale-invariant feature transform (SIFT)that the calculation is large and the process is time ...
Gaoqing Cheng, Jiaxing Chen
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A novel local feature descriptor for image matching
2008 IEEE International Conference on Multimedia and Expo, 2008Image matching is a fundamental task of many problems in computer vision. This paper presents a novel local feature descriptor based on the gradient distance and orientation histogram (GDOH), which can be used for reliably matching between different views of a scene for wide baseline.
Heng Yang 0003, Qing Wang 0006
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A locally based feature descriptor for abnormalities detection
Soft Computing, 2019Wireless capsule endoscopy (WCE) is a novel imaging technique that can view the entire small bowel in human body. Therefore, it has been gradually adopted compared with traditional endoscopies for gastrointestinal diseases. However, the task of reviewing the vast amount of images produced by a WCE test is exhaustive for the physicians.
Said Charfi, Mohamed El Ansari
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Learning Local Feature Descriptors for Multiple Object Tracking
2021The present study aims at learning class-agnostic embedding, which is suitable for Multiple Object Tracking (MOT). We demonstrate that the learning of local feature descriptors could provide a sufficient level of generalization. Proposed embedding function exhibits on-par performance with its dedicated person re-identification counterparts in their ...
Dmytro Mykheievskyi +2 more
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A novel biologically inspired local feature descriptor
Biological Cybernetics, 2014Local feature descriptor is a fundamental representation for image patch which has been extensively used in many computer vision applications. In this paper, different from state-of-the-art features, a novel biologically inspired local descriptor (BILD) is proposed based on the visual information processing mechanism of ventral pathway in human brain ...
Yun Zhang +4 more
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CDIKP: A highly-compact local feature descriptor
2008 19th International Conference on Pattern Recognition, 2008A new feature descriptor is presented for object and scene recognition. The new approach, called CDIKP, uniquely combines the scale-invariant feature detection with a robust projection kernel technique to produce highly efficient feature representation.
Yun-Ta Tsai, Quan Wang 0001, Suya You
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A Local Feature Descriptor based on Improved Codebook Model
2020 6th International Symposium on System and Software Reliability (ISSSR), 2020The following topics are dealt with: learning (artificial intelligence); pattern classification; program testing; feature extraction; neural nets; formal specification; security of data; software maintenance; avionics; Bluetooth.
Qinggang Wu, Xuming Zhai, Baohua Yue
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An improved local feature descriptor based on SIFT
Proceedings of the Second International Conference on Internet Multimedia Computing and Service, 2010Constructing proper descriptors for interest points is a critical aspect for local features related tasks in some computer vision and pattern recognition. This paper proposed to improve the SIFT descriptor by means of combining the second derivative and the gradient magnitude, introducing the polar histogram orientation bin, as well as expending the ...
Kaiyang Liao, Guizhong Liu
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Action recognition via local descriptors and holistic features
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2009In this paper we propose a unified action recognition framework fusing local descriptors and holistic features. The motivation is that the local descriptors and holistic features emphasize different aspects of actions and are suitable for the different types of action databases.
Xinghua Sun +2 more
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