The DOI matches its Crossref record; 44 of the 50 references it cites were found in a registry or an index.
Distinctive Image Features from Scale-Invariant Keypoints
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Moreover, the efficiency of HF-net2 was tested and compared with several wellknown handcrafted algorithms for keypoint detection and description including Harris [4], FAST [6], SIFT [9] and ORB [8].”
From Keypoint Detection and Description through Deep Learning in Unstructured Environments (2023) · cites this paper as [9]
In the citing paper
“By including a background removal step sim-330 ilar to the WGE in [9], which makes use of a Prewitt operator in combination with a gradient filter, the authors could also demonstrate the robustness of their IP with respect to the Earth in the background.”
From Review of the robustness and applicability of monocular pose estimation systems for relative navigation with an uncooperative spacecraft (2019) · cites this paper as [32]
In the citing paper
“Feature fusion was then used to synthesise the detected points into polylines which resemble parts of the spacecraft body.”
From Review of the robustness and applicability of monocular pose estimation systems for relative navigation with an uncooperative spacecraft (2019) · cites this paper as [32]
In the citing paper
“Alternatively, Capuano et al. [32] introduced a new IP scheme in which three different parallel processing streams, which use the Shi-Tommasi (ST) corners detector, the HT, and the Line Segment Detector (LSD), are exploited in order to filter three sets of points and improve the robustness of the feature detection.”
From Review of the robustness and applicability of monocular pose estimation systems for relative navigation with an uncooperative spacecraft (2019) · cites this paper as [32]
In the citing paper
“Furthermore, the scenarios with the Earth horizon were tackled by tuning the threshold of gradient filter to a more selective value.”
From Review of the robustness and applicability of monocular pose estimation systems for relative navigation with an uncooperative spacecraft (2019) · cites this paper as [32]
In the citing paper
“Robustness proven”
From Review of the robustness and applicability of monocular pose estimation systems for relative navigation with an uncooperative spacecraft (2019) · cites this paper as [32]
In the citing paper
“Although pyramid decomposition has been widely used in image compression [8], computer vision [9], etc., its use in image hashing, as proposed in this paper, has proved to be every effective.”
From A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids (2019) · cites this paper as [9]
In the citing paper
“The latter, introduced by Lowe [2], have been shown to outperform the others [7].”
From SURF: Speeded Up Robust Features (2006) · cites this paper as [2]
In the citing paper
“This can be explained by the fact that they capture a substantial amount of information about the spatial intensity patterns, while at the same time being robust to small deformations or localisation errors.”
From SURF: Speeded Up Robust Features (2006) · cites this paper as [2]
In the citing paper
“While all of the above metrics rely upon gradient magnitudes, gradient orientation on its own has been widely used for feature matching (Lowe 2004), object detection (Dalal and Triggs 2005), and image registration (De Nigris et al 2012), and shown promise in robust matching under partial occlusion and view point changes.”
From 3D–2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch (2016) · cites this paper as Lowe 2004
In the citing paper
“Traditional methods may require complex feature matching algorithms (e.g., SIFT, SURF) or additional classifiers (e.g., SVM), whereas the MobileNetV2 network model directly utilizes features extracted by the deep learning model to perform comparison, which simplifies the process [27,28].”
From Digital Image Copyright Protection and Management Approach—Based on Artificial Intelligence and Blockchain Technology (2025) · cites this paper as [27]
Citations
Cites
Multiple View Geometry in Computer Vision
Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070
Object recognition from local scale-invariant features
Lowe, D. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790410 · Cited by 16,472
Self-citationA Combined Corner and Edge Detector
Harris, C., & Stephens, M. (1988) · Procedings of the Alvey Vision Conference 1988 · doi:10.5244/c.2.23 · Cited by 12,901
Generalizing the Hough transform to detect arbitrary shapes
Ballard, D. H. (1981) · Pattern Recognition · doi:10.1016/0031-3203(81)90009-1 · Cited by 4,434
Robust wide-baseline stereo from maximally stable extremal regions
Matas, J., Chum, O., Urban, M., & Pajdla, T. (2004) · Image and Vision Computing · doi:10.1016/j.imavis.2004.02.006 · Cited by 3,764
An Algorithm for Finding Best Matches in Logarithmic Expected Time
Friedman, J. H., Bentley, J. L., & Finkel, R. A. (1977) · ACM Transactions on Mathematical Software · doi:10.1145/355744.355745 · Cited by 2,802
Koenderink, J. J. (1984) · Biological Cybernetics · doi:10.1007/bf00336961 · Cited by 2,452
Witkin, A. (1987) · Elsevier eBooks · doi:10.1016/b978-0-08-051581-6.50036-2 · Cited by 2,375
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Arya, S., Mount, D. M., Netanyahu, N. S., Silverman, R., & Wu, A. Y. (1998) · Journal of the ACM · doi:10.1145/293347.293348 · Cited by 2,290
Object class recognition by unsupervised scale-invariant learning
Fergus, R., Perona, P., & Zisserman, A. (2003) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2003.1211479 · Cited by 2,046
Research works printed but not linked: 3
- Harris, C. and Stephens, M. 1988. Acombined corner and edge detector. In Fourth Alvey Vision Conference, Manchester, UK, pp. 147–151.
- Mikolajczyk, K. 2002. Detection of local features invariant to affine transformations, Ph.D. thesis, Institut National Polytechnique de Grenoble, France.
- Torr, P. 1995. Motion segmentation and outlier detection, Ph.D. Thesis, Dept. of Engineering Science, University of Oxford, UK.
Cited by
Sorted by citations
Items 27,401–27,500 of 56,201
Yücel, M. A., & Yücel, D. Ş. (2023) · Environmental Monitoring and Assessment · doi:10.1007/s10661-023-11182-0 · Cited by 6
Xu, Y., Feng, L., Xia, Z., et al. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-89134-3_11 · Cited by 6
A More Effective Method for Image Representation: Topic Model Based on Latent Dirichlet Allocation
Li, Z., Tian, W., Li, Y., et al. (2015) · International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics) · doi:10.1109/cadgraphics.2015.19 · Cited by 6
Video concept detection by audio-visual grouplets
Jiang, W., & Loui, A. C. P. (2012) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-012-0020-6 · Cited by 6
Place Recognition via 3D Modeling for Personal Activity Lifelog Using Wearable Camera
Wannous, H., Dovgalecs, V., Mégret, R., et al. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-27355-1_24 · Cited by 6
Image-Based Mobile Robot Guidance System by Using Artificial Ceiling Landmarks
Shih, C.-L., & Ku, Y.-T. (2016) · Journal of Computer and Communications · doi:10.4236/jcc.2016.411001 · Cited by 6
Vreeswijk, D. T. J., Snoek, C. G. M., van de Sande, K. E. A., & Smeulders, A. W. M. (2012) · International Conference on Multimedia Retrieval · doi:10.1145/2324796.2324806 · Cited by 4
Semantic-aware Representation Learning for Homography Estimation
Liu, Y., Huang, Q., Hui, S., Fu, J., Zhou, S., Wu, K., Li, P., & Wang, J. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681021 · Cited by 7
“SIFT [28] features exhibit invariance to rotation and scale.”
BackgroundMethodActive learning for image retrieval via visual similarity metrics and semantic features
Casado-Coscolla, A., Sánchez-Belenguer, C., Wolfart, E., Carlos, A. B., & Sequeira, V. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.109239 · Cited by 7
Sun, B., Xu, F., Zhou, G., et al. (2015) · Journal of Electronic Imaging · doi:10.1117/1.jei.24.1.013018 · Cited by 6
Neural Light Spheres for Implicit Image Stitching and View Synthesis
Chugunov, I., Joshi, A., Murthy, K., et al. (2024) · SIGGRAPH Asia Conference Papers · doi:10.1145/3680528.3687660 · Cited by 6
Select informative features for recognition
Wang, Z., Zhao, Q., Chu, D. C. Y., et al. (2011) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2011.6116163 · Cited by 6
Bags of spatial relations and shapes features for structural object description
Clément, M., Kurtz, C., & Wendling, L. (2016) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2016.7899929 · Cited by 7
Deformed contour segment matching for multi-source images
Wu, Q., Xu, G., Cheng, Y., et al. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.107968 · Cited by 6
Wan, S., Sun, S., Bhattacharya, S., et al. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24553-9_52 · Cited by 6
Object detection using voting spaces trained by few samples
Xu, P., Ye, M., Li, X., et al. (2013) · Optical Engineering · doi:10.1117/1.oe.52.9.093105 · Cited by 6
Inoue, K., & Kise, K. (2009) · doi:10.1109/iccvw.2009.5457544 · Cited by 6
Measuring the Main Parameters of the Human Body in Images by Canny Edge Detector
Mojarrad, M. (2013) · Science Journal of Circuits Systems and Signal Processing · doi:10.11648/j.cssp.20130205.11 · Cited by 6
Visual odometry using RGB-D camera on ceiling vision
Wang, H., Mou, W., Suratno, H., et al. (2012) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio.2012.6491051 · Cited by 6
Treasure hunting for humanoids robot
Stasse, O., Foissotte, T., Larlus, D., et al. (2008) · Cited by 6
Ahadullah, M., Sapar, S. H., Al-Saidi, N. M. G., et al. (2020) · IEEE Access · doi:10.1109/access.2020.3044290 · Cited by 6
Feature Based Automatic Stitching of Microscopic Images
Fan, X., & Xia, S. (2007) · Springer eBooks · doi:10.1007/978-3-540-74282-1_88 · Cited by 6
New point matching algorithm for panoramic reflectance images
Kang, Z., & Zlatanova, S. (2007) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.751570 · Cited by 6
Wide Baseline Stereo Matching with Convex Bounded Distortion Constraints
Galun, M., Amir, T., Hassner, T., et al. (2015) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.257 · Cited by 6
Lindeberg, T. (2020) · Springer eBooks · doi:10.1007/978-3-030-03243-2_242-1 · Cited by 6
Gao, C., Sang, N., & Huang, R. (2016) · Information Sciences · doi:10.1016/j.ins.2016.08.035 · Cited by 6
DGD-net: Local Descriptor Guided Keypoint Detection Network
Liu, X., Meng, C., Tian, F.-P., et al. (2021) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme51207.2021.9428406 · Cited by 6
Extraction of intersecting palm‐vein and palmprint features for cancellable identity verification
Lee, J., Oh, B., & Toh, K. (2024) · CAAI Transactions on Intelligence Technology · doi:10.1049/cit2.12277 · Cited by 6
Differential Optical Flow Estimation Under Monocular Epipolar Line Constraint
Mohamed, M. A., Mirabdollah, M. H., & Mertsching, B. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-20904-3_32 · Cited by 6
Scene Categorization Through Combining LBP and SIFT Features Effectively
Bai, S., Hou, J., & Ohnishi, N. (2015) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s0218001416550016 · Cited by 6
Machine Learning-Based Highway Truck Commodity Classification Using Logo Data
He, P. L., Wu, A., Huang, X., et al. (2022) · Applied Sciences · doi:10.3390/app12042075 · Cited by 6
ShuiAttNet: Fully convolutional attention network for Shuishu character recognition
Bi, X., Han, L., & Qiao, W. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.127613 · Cited by 8
An Approach to Human-Robot Collaborative Drilling and Fastening in Aerospace Final Assembly
Johnson, M., Liu, R., Gopalan, N., et al. (2021) · AIAA SciTech Forum · doi:10.2514/6.2021-0270 · Cited by 6
Body-based human age estimation at a distance
Ge, Y., Lu, J., Feng, X., et al. (2013) · IEEE International Conference on Multimedia and Expo workshops · doi:10.1109/icmew.2013.6618302 · Cited by 6
A Video Image Compression Method based on Visually Salient Features
Ke, H., Sun, H., Gao, L., et al. (2014) · Journal of Digital Information Management · Cited by 6
A Picture Is Worth a Thousand Tags: Automatic Web Based Image Tag Expansion
Gilbert, A., & Bowden, R. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-37444-9_35 · Cited by 6
Tone Correction with Dynamic Objects for Seamless Image Mosaic
Shin, Y.-H., Park, M.-G., Jeon, Y.-S., et al. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-35740-4_9 · Cited by 6
A Cross-Platform OpenVX Library for FPGA Accelerators
Dávila-Guzmán, M. A., Tejero, R. G., Villarroya-Gaudó, M., et al. (2021) · Proceedings - Euromicro Workshop on Parallel and Distributed Processing/Proceedings · doi:10.1109/pdp52278.2021.00020 · Cited by 6
Test-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on Predicted-View Synthesis
Pérez-Villar, J. I. B., García‐Martín, Á., Bescós, J., & SanMiguel, J. C. (2024) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2024.3410956 · Cited by 6
“This approach is proposed in [24], where a set of scale invariant feature transform (SIFT) [25] keypoints and descriptors are employed in combination with a PnP solver to retrieve the spacecraft pose.”
MethodDistributed Index for Matching Multimedia Objects
Abdelsadek-Ahmed, A. M. (2014) · Summit (Simon Fraser University) · Cited by 6
Enhanced correlation coefficient as a refinement of image registration
Hwooi, S. K. W., & Sabri, A. Q. M. (2017) · IEEE International Conference on Signal and Image Processing Applications (ICSIPA) · doi:10.1109/icsipa.2017.8120609 · Cited by 6
Vector Road Map Registration to Oblique Wide Area Motion Imagery by Exploiting Vehicle Movements
Elliethy, A. S., & Sharma, G. (2016) · Electronic Imaging · doi:10.2352/issn.2470-1173.2016.3.vstia-520 · Cited by 6
Image registration using modified adaptive polar transform
Sasikala, D., & Neelaveni, R. (2010) · Procedia Computer Science · doi:10.1016/j.procs.2010.11.042 · Cited by 6
Deconstructing multimodality: visual properties and visual context in human semantic processing
Davis, C. M., Bulat, L., Verő, A. L., & Shutova, E. (2019) · Joint Conference on Lexical and Computational Semantics · doi:10.18653/v1/s19-1013 · Cited by 6
Holte, M. B. (2014) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2014.7026160 · Cited by 6
An Algorithm for Stitching Images with Different Contrast and Elimination of Ghost
Su, H., Wang, J., Li, Y., et al. (2014) · International Symposium on Computational Intelligence and Design · doi:10.1109/iscid.2014.75 · Cited by 6
Information processing for live photo mosaic with a group of wireless image sensors
Li, F., Barabas, J., & Santos, A. L. (2010) · ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) · doi:10.1145/1791212.1791220 · Cited by 6
Photo-to-Sketch Transformation in a Complex Background
Zhang, X., Li, X., Ouyang, S., et al. (2017) · IEEE Access · doi:10.1109/access.2017.2707394 · Cited by 6
Speeding Up Structure from Motion on Large Scenes Using Parallelizable Partitions
Douterloigne, K., Gautama, S., & Philips, W. R. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-17691-3_2 · Cited by 6
A Novel Method for Automated Lung Region Segmentation in Chest X-Ray Images
Matsuyama, E. (2021) · Journal of Biomedical Science and Engineering · doi:10.4236/jbise.2021.146024 · Cited by 6
Rover-Based Surface and Subsurface Modeling for Planetary Exploration
Furgale, P. T., Barfoot, T., & Ghafoor, N. (2010) · Springer tracts in advanced robotics · doi:10.1007/978-3-642-13408-1_45 · Cited by 6
Mu, K., Wang, W., Liu, H., Liang, L., & Zhang, S. (2025) · Remote Sensing · doi:10.3390/rs17061071 · Cited by 6
Fashion Finder: A System for Locating Online Stores on Instagram from Product Images
Lodkaew, T., Supsohmboon, W., Pasupa, K., et al. (2018) · doi:10.1109/iciteed.2018.8534871 · Cited by 6
Coarse-to-fine global localization for mobile robots with hybrid maps of objects and spatial layouts
Park, S., Cheong, H., & Park, S.-K. (2009) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2009.5354193 · Cited by 6
Approximated Overlap Error for the Evaluation of Feature Descriptors on 3D Scenes
Bellavia, F., Valenti, C. F., Lupaşcu, C. A., et al. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-41181-6_28 · Cited by 6
Affine-invariant SIFT descriptor with global context
Cao, B., Ma, C., & Liu, Z. (2010) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp.2010.5647071 · Cited by 6
A probabilistic model for recursive factorized image features
Karayev, S., Fritz, M., Fidler, S., et al. (2011) · doi:10.1109/cvpr.2011.5995728 · Cited by 6
Simultaneous Localization and Mapping (SLAM) : towards an autonomous search and rescue aiding drone
Heukels, F. R. (2015) · Cited by 6
High-Precision Satellite Video Stabilization Method Based on ED-RANSAC Operator
Zhang, F., Li, X., Wang, T., et al. (2023) · Remote Sensing · doi:10.3390/rs15123036 · Cited by 6
PLMP – Point-Line Minimal Problems in Complete Multi-View Visibility
Duff, T., Kohn, K., Leykin, A., et al. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3324728 · Cited by 6
Composite Object Relation Modeling for Few-Shot Scene Recognition
Song, X., Liu, C., Zeng, H., Zhu, Y., Chen, G., Qin, X., & Jiang, S. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3321475 · Cited by 6
Automatic Registration of Large-Scale Multi-sensor Datasets
Wang, Q., & You, S. O. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-35740-4_18 · Cited by 6
Morphology-Retained Non-Linear Image Registration of Serial Electron Microscopy Sections
Chen, X., Xie, Q., Shen, L., et al. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451280 · Cited by 6
Multiple Instances Detection in RGBD Images
Haladová, Z. B., & Šikudová, E. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11331-9_30 · Cited by 6
Estimating in-plane rotation angle for face images from multi-poses
Anvar, S. M. H., Yau, W., Nandakumar, K., et al. (2013) · doi:10.1109/cibim.2013.6607914 · Cited by 6
Object instance identification with fully convolutional networks
Portaz, M., Kohl, M., Chevallet, J., Quenot, G. M., & Mulhem, P. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-5798-7 · Cited by 6
Aerial Implicit 3D Video Stabilization Using Epipolar Geometry Constraint
Huynh, L., Choi, J., & Medioni, G. (2014) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2014.600 · Cited by 6
DeepACO: A Robust Deep Learning-based Automatic Checkout System
Pham, L. H., Tran, D. N., Nguyen, H.-H., Tran, T. H.-P., Jeon, H., Jeon, H.-M., & Jeon, J. W. (2022) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw56347.2022.00350 · Cited by 6
A Visual Positioning Method of UAV in a Large-Scale Outdoor Environment
Zhao, C., Wu, D., He, J., et al. (2023) · Sensors · doi:10.3390/s23156941 · Cited by 6
A THREE-DIMENSIONAL SIMULATION AND VISUALIZATION SYSTEM FOR UAV PHOTOGRAMMETRY
Liang, Y., Qu, Y., & Cui, T. (2017) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xlii-2-w6-217-2017 · Cited by 6
Cascade Network with Guided Loss and Hybrid Attention for Finding Good Correspondences
Chen, Z., Yang, F., & Tao, W. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i2.16198 · Cited by 6
Adaptive object detection by implicit sub-class sharing features
Zhang, S., Li, N., Cheng, X., et al. (2012) · Signal Processing · doi:10.1016/j.sigpro.2012.11.027 · Cited by 6
Toward Compressed 3D Descriptors
Malaguti, F., Tombari, F., Salti, S., Pau, D. P., & Stefano, L. D. (2012) · International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission · doi:10.1109/3dimpvt.2012.9 · Cited by 6
Brunner, D. (2009) · Unitn-eprints PhD (University of Trento) · Cited by 6
Packed Dense Interest Points for Scene Image Retrieval
Wang, H., Teng, P., & Liang, W. G. (2011) · International Conference on Image and Graphics · doi:10.1109/icig.2011.148 · Cited by 6
Automatic lesion detection for narrow-band imaging bronchoscopy
Daneshpajooh, V., Ahmad, D., Toth, J. W., et al. (2024) · Journal of medical imaging · doi:10.1117/1.jmi.11.3.036002 · Cited by 6
The Integration of the Image Sensor with a 3-DOF Pneumatic Parallel Manipulator
Lin, H.-T., & Chiang, M.-H. (2016) · Sensors · doi:10.3390/s16071026 · Cited by 6
Conditional Attention for Content-based Image Retrieval
Hu, Z., & Borş, A. G. (2020) · British Machine Vision Conference (BMVC) · doi:10.5244/c.34.92 · Cited by 8
Zhong, J., Li, M., Gruen, A., et al. (2024) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-x-2-2024-247-2024 · Cited by 6
“The classic ratio-test (Lowe, 2004) matches features based on the similarity between descriptors.”
BackgroundMethodInfluentialContent-Based Image Retrieval via Subspace-Projected Salient Features
Huang, J., Zia, A., Zhou, J. W., & Robles‐Kelly, A. (2008) · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · doi:10.1109/dicta.2008.29 · Cited by 6
Sift approach matching constraints for real-time attention responsive system
Shi, F., Gale, A. G., & Purdy, K. J. (2006) · Loughborough University Institutional Repository (Loughborough University) · Cited by 6
Shu, Y., Feng, Y., Wu, G., et al. (2019) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-019-02080-0 · Cited by 6
Hasheminasab, S. M., Zhou, T., Lin, Y.-C., et al. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3167378 · Cited by 6
Retaining Image Feature Matching Performance Under Low Light Conditions
Shyam, P., Bangunharcana, A., & Kim, K.-S. (2020) · International Conference on Control, Automation and Systems (ICCAS) · doi:10.23919/iccas50221.2020.9268426 · Cited by 8
A Parameter-free Multi-view Information Bottleneck Clustering Method by Cross-view Weighting
Hu, S., Geng, R., Cheng, Z., et al. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3547985 · Cited by 6
Fast keypoint detection in video sequences
Baroffio, L., Cesana, M., Redondi, A. E. C., et al. (2016) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2016.7471895 · Cited by 6
Local Color Descriptor for Object Recognition across Illumination Changes
Song, X., Muselet, D., & Trémeau, A. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04697-1_56 · Cited by 6
Benlakhdar, S., Rziza, M., & Thami, R. O. H. (2020) · Biomedical & Pharmacology Journal · doi:10.13005/bpj/2041 · Cited by 6
Ensemble of Convolutional Neural Networks for Face Recognition
Mohanraj, V., Chakkaravarthy, S. S., & Vaidehi, V. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-981-13-1280-9_43 · Cited by 6
Colorimetric Correction for Stereoscopic Camera Arrays
Mouffranc, C., & Nozick, V. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-37410-4_18 · Cited by 6
John, C., Shilling, F. M., & Post, E. (2021) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13730 · Cited by 6
Dong, Y., Jiao, W., Long, T., et al. (2019) · Sensors · doi:10.3390/s19102329 · Cited by 6
Forest hashing: Expediting large scale image retrieval
Springer, J., Xin, X., Zhu, L., et al. (2013) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2013.6637938 · Cited by 6
Robust Laser Speckle Authentication System through Data Mining Techniques
Yeh, C., Lee, G., & Lin, C. (2015) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2015.2400411 · Cited by 6
A fast binary encoding mechanism for approximate nearest neighbor search
Zhao, H., Wang, Z., Liu, P., & Wu, B. (2015) · Neurocomputing · doi:10.1016/j.neucom.2015.09.110 · Cited by 6
Automatic Carotid Artery Detection Using Attention Layer Region-Based Convolution Neural Network
Wang, X.-Y., Zhong, X., Xia, M., Jiang, W., Huang, X., Gu, Z., & Huang, X.-S. (2019) · Int. J. Humanoid Robotics · doi:10.1142/s0219843619500154 · Cited by 4
Ben, K., Bouhorma, M., & Ben, M. (2016) · International Journal of Computer Applications · doi:10.5120/ijca2016911880 · Cited by 6
Holistic Feature Extraction for Automatic Image Annotation
Sarin, S., Fahrmair, M., Wagner, M. W., et al. (2011) · doi:10.1109/mue.2011.22 · Cited by 6
On detection of edges and interest points for omnidirectional images in spherial domain
Serce, H., Bastanlar, Y., Temizel, A., et al. (2008) · doi:10.1109/siu.2008.4632658 · Cited by 6
Towards Real-time 3D Visualization with Multiview RGB Camera Array
Ke, J., Watras, A. J., Kim, J.-J., et al. (2022) · Journal of Signal Processing Systems · doi:10.1007/s11265-021-01729-0 · Cited by 6
Metadata
- Authors
- Lowe, D. G.
- Affiliations
- University of British Columbia (CA)
- Corresponding author
- Lowe, David G.
- ORCID
- Lowe, David G.
- Venue
- International Journal of Computer Vision
- Published
- 2004-11
- Volume
- 60
- Issue
- 2
- Pages
- 91-110
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W2151103935
- Semantic Scholar
- 8c04f169203f9e55056a6f7f956695babe622a38
- Cited by
- 55,589
- References
- 50
- Citations by year
- 2026: 1480 · 2025: 2400 · 2024: 2519 · 2023: 2604 · 2022: 2705 · 2021: 3066 · 2020: 2933 · 2019: 3240 · 2018: 3232 · 2017: 3363 · 2016: 3431 · 2015: 3747 · 2014: 3569 · 2013: 3333 · 2012: 3003
- FWCI
- 699.25
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Journal of Computer Vision (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Keywords
- feature matching, affine invariance, rotation invariance, object recognition, nearest neighbor matching, Hough transform, pose estimation, occlusion
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review