7.1.10.9 Evaluation of Salient Point, Interest Point Detection

Chapter Contents (Back)
Interest Points. Salient Points. Feature Points. Evaluation, Feature Points.

Schmid, C.[Cordelia], Mohr, R.[Roger], and Bauckhage, C.[Christian],
Evaluation of Interest Point Detectors,
IJCV(37), No. 2, June 2000, pp. 151-172.
DOI Link 0008
BibRef
Earlier:
Comparing and Evaluating Interest Points,
ICCV98(230-235).
IEEE DOI BibRef

Gil, A.[Arturo], Martinez Mozos, O.[Oscar], Ballesta, M.[Monica], Reinoso, O.[Oscar],
A comparative evaluation of interest point detectors and local descriptors for visual SLAM,
MVA(21), No. 6, October 2010, pp. 905-920.
WWW Link. 1011
BibRef

Gauglitz, S.[Steffen], Höllerer, T.[Tobias], Turk, M.A.[Matthew A.],
Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking,
IJCV(94), No. 3, September 2011, pp. 335-360.
WWW Link.
WWW Link. 1101
Dataset, Tracking. Present a dataset with ground truth for evaluation. And evaluation of camera tracking. BibRef

Kazmi, W.[Wajahat], Andersen, H.J.[Hans Jřrgen],
A comparison of interest point and region detectors on structured, range and texture images,
JVCIR(32), No. 1, 2015, pp. 156-169.
Elsevier DOI 1511
Affine invariant regions BibRef

Rey-Otero, I.[Ives], Delbracio, M.[Mauricio],
Is Repeatability an Unbiased Criterion for Ranking Feature Detectors?,
SIIMS(8), No. 4, 2015, pp. 2558-2580.
DOI Link 1601
BibRef

Rey-Otero, I.[Ives], Delbracio, M.[Mauricio], Morel, J.M.[Jean-Michel],
Comparing feature detectors: A bias in the repeatability criteria,
ICIP15(3024-3028)
IEEE DOI 1512
BibRef
Earlier: A1, A3, A2:
An analysis of scale-space sampling in SIFT,
ICIP14(4847-4851)
IEEE DOI 1502
Feature detectors; performance evaluation. Cameras BibRef

Ehsan, S.[Shoaib], Clark, A.F.[Adrian F.], Leonardis, A.[Ales], ur Rehman, N.[Naveed], Khaliq, A.[Ahmad], Fasli, M.[Maria], McDonald-Maier, K.D.[Klaus D.],
A Generic Framework for Assessing the Performance Bounds of Image Feature Detectors,
RS(8), No. 11, 2016, pp. 928.
DOI Link 1612
BibRef

Danaci, E.G.[Emine Gul], Ikizler-Cinbis, N.[Nazli],
Low-level features for visual attribute recognition: An evaluation,
PRL(84), No. 1, 2016, pp. 185-191.
Elsevier DOI 1612
Visual attributes BibRef

Madeo, S., Bober, M.,
Fast, Compact, and Discriminative: Evaluation of Binary Descriptors for Mobile Applications,
MultMed(19), No. 2, February 2017, pp. 221-235.
IEEE DOI 1702
feature extraction BibRef

Duthon, P.[Pierre], Bernardin, F.[Frédéric], Chausse, F.[Frédéric], Colomb, M.[Michčle],
Benchmark for the robustness of image features in rainy conditions,
MVA(29), No. 5, July 2018, pp. 915-927.
Springer DOI 1808
Eight of the most representative image features in a road environment are selected on the basis of a literature review. BibRef

Balntas, V.[Vassileios], Lenc, K.[Karel], Vedaldi, A.[Andrea], Tuytelaars, T.[Tinne], Matas, J.G.[Jiri G.], Mikolajczyk, K.[Krystian],
H-Patches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors,
PAMI(42), No. 11, November 2020, pp. 2825-2841.
IEEE DOI 2010
BibRef
Earlier: A1, A2, A3, A6, Only: CVPR17(3852-3861)
IEEE DOI 1711
Dataset, Local Descriptors. HPatches dataset. Benchmark testing, Detectors, Protocols, Task analysis, Feature extraction, Training, Image matching, Local features, patch classification. Feature extraction, Protocols, Size, measurement BibRef

Liu, Y.T.[Yun-Tao], Dou, Y.[Yong], Qiao, P.[Peng],
Beyond top-N accuracy indicator: a comprehensive evaluation indicator of CNN models in image classification,
IET-CV(14), No. 6, September 2020, pp. 407-414.
DOI Link 2010
Evaluation, Object Detection. Better evaluations needed. BibRef

Uchinoura, S.[Shinji], Kurita, T.[Takio],
Improved Head and Data Augmentation to Reduce Artifacts at Grid Boundaries in Object Detection,
IEICE(E107-D), No. 1, January 2024, pp. 115-124.
WWW Link. 2401
Evaluation, Object Detection. object detector class scores drop when the target object center is at the grid boundary BibRef


Mao, X.F.[Xiao-Feng], Chen, Y.F.[Yue-Feng], Zhu, Y.[Yao], Chen, D.[Da], Su, H.[Hang], Zhang, R.[Rong], Xue, H.[Hui],
COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts,
ICCV23(6316-6327)
IEEE DOI Code:
WWW Link. 2401
BibRef

Boreiko, V.[Valentyn], Hein, M.[Matthias], Metzen, J.H.[Jan Hendrik],
Identifying Systematic Errors in Object Detectors with the SCROD Pipeline,
BRAVO23(4092-4101)
IEEE DOI 2401
BibRef

Le, Q.T.[Quyet-Tien], Ladret, P.[Patricia], Nguyen, H.T.[Huu-Tuan], Caplier, A.[Alice],
Large Field/Close-Up Image Classification: From Simple to Very Complex Features,
CAIP19(II:532-543).
Springer DOI 1909
Evaluation of features. Exchangeable Image File (EXIF) features, handcrafted features and learned features. Learned are effective, but expensive to compute, EXIF does reasonably well with less cost. BibRef

Tomaselli, V.[Valeria], Plebani, E.[Emanuele], Strano, M.[Mauro], Pau, D.[Danilo],
Complexity and Accuracy of Hand-Crafted Detection Methods Compared to Convolutional Neural Networks,
CIAP17(I:298-308).
Springer DOI 1711
BibRef

Schönberger, J.L., Hardmeier, H., Sattler, T., Pollefeys, M.,
Comparative Evaluation of Hand-Crafted and Learned Local Features,
CVPR17(6959-6968)
IEEE DOI 1711
Benchmark testing, Detectors, Image reconstruction, Measurement, Neural, networks BibRef

Cordes, K.[Kai], Grundmann, L.[Lukas], Ostermann, J.[Jörn],
Feature Evaluation with High-Resolution Images,
CAIP15(I:374-386).
Springer DOI 1511
BibRef

Chen, Y.L.[Yi-Lei], Hsu, C.T.[Chiou-Ting],
Implicit Rank-Sparsity Decomposition: Applications to Saliency/Co-saliency Detection,
ICPR14(2305-2310)
IEEE DOI 1412
Equations BibRef

Figat, J.[Jan], Kornuta, T.[Tomasz], Kasprzak, W.[Wlodzimierz],
Performance Evaluation of Binary Descriptors of Local Features,
ICCVG14(187-194).
Springer DOI 1410
BibRef

Dzulfahmi, Ohta, N.,
Performance Evaluation of Image Feature Detectors and Descriptors for Outdoor-Scene Visual Navigation,
ACPR13(872-876)
IEEE DOI 1408
image matching BibRef

Bekele, D.[Dagmawi], Teutsch, M.[Michael], Schuchert, T.[Tobias],
Evaluation of binary keypoint descriptors,
ICIP13(3652-3656)
IEEE DOI 1402
binary descriptors BibRef

Zambanini, S.[Sebastian], Kampel, M.[Martin],
Evaluation of Low-Level Image Representations for Illumination-Insensitive Recognition of Textureless Objects,
CIAP13(I:71-80).
Springer DOI 1311
BibRef
And:
A Local Image Descriptor Robust to Illumination Changes,
SCIA13(11-21).
Springer DOI 1311
dataset with rendered images of 3D models. Low level features for surface characteristics. BibRef

Miksik, O.[Ondrej], Mikolajczyk, K.[Krystian],
Evaluation of local detectors and descriptors for fast feature matching,
ICPR12(2681-2684).
WWW Link. 1302
BibRef

Heinly, J.[Jared], Dunn, E.[Enrique], Frahm, J.M.[Jan-Michael],
Comparative Evaluation of Binary Features,
ECCV12(II: 759-773).
Springer DOI 1210
BibRef

Lankinen, J.[Jukka], Kangas, V.[Ville], Kamarainen, J.K.[Joni-Kristian],
A comparison of local feature detectors and descriptors for visual object categorization by intra-class repeatability and matching,
ICPR12(780-783).
WWW Link. 1302
BibRef

Gat, C.[Christopher], Albu, A.B.[Alexandra Branzan], German, D.[Daniel], Higgs, E.[Eric],
A Comparative Evaluation of Feature Detectors on Historic Repeat Photography,
ISVC11(II: 701-714).
Springer DOI 1109
BibRef

Huynh, D.Q., Saini, A., Liu, W.[Wei],
Evaluation of three local descriptors on low resolution images for robot navigation,
IVCNZ09(113-118).
IEEE DOI 0911
BibRef

Stöttinger, J.[Julian], Donner, R.[René], Szumilas, L.[Lech], Hanbury, A.[Allan],
Evaluation of Gradient Vector Flow for Interest Point Detection,
ISVC08(I: 338-348).
Springer DOI 0812
BibRef

Reiterer, A., Eiter, T.,
A Distance-Based Method for the Evaluation of Interest point Detection Algorithms,
ICIP06(2745-2748).
IEEE DOI 0610
BibRef

Apollonio, F.I., Ballabeni, A., Gaiani, M., Remondino, F.,
Evaluation of feature-based methods for automated network orientation,
CloseRange14(47-54).
DOI Link 1411
evaluate some feature-based methods used to automatically extract tie points BibRef

Remondino, F.[Fabio],
Detectors and Descriptors for Photogrammetric Applications,
PCV06(xx-yy).
PDF File. 0609
Interest operators for aerial iamges. BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Contourlet Representations and Processing .


Last update:Nov 26, 2024 at 16:40:19