Evaluation of Interest Point Detectors

Many different low-level feature detectors exist and it is widely agreed that the evaluation of detectors is important. In this paper we introduce two evaluation criteria for interest points' repeatability rate and information content. Repeatability rate evaluates the geometric stability under different transformations. Information content measures the distinctiveness of features. Different interest point detectors are compared using these two criteria. We determine which detector gives the best results and show that it satisfies the criteria well.

[1]  J. G. Semple,et al.  Algebraic Projective Geometry , 1953 .

[2]  Hans P. Morevec.  Towards automatic visual obstacle avoidance , 1977, IJCAI 1977.

[3]  Hans P. Moravec.  Towards Automatic Visual Obstacle Avoidance , 1977, IJCAI.

[4]  Paul Beaudet,et al.  Rotationally invariant image operators , 1978 .

[5]  Hans-Hellmut Nagel,et al.  Volumetric model and 3D trajectory of a moving car derived from monocular TV frame sequences of a street scene , 1981, Comput. Graph. Image Process..

[6]  Hans-Hellmut Nagel,et al.  Displacement vectors derived from second-order intensity variations in image sequences , 1983, Comput. Vis. Graph. Image Process..

[7]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[8]  Michael Brady,et al.  The Curvature Primal Sketch , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Farzin Mokhtarian,et al.  Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  G. Medioni,et al.  Corner detection and curve representation using cubic B-splines , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[12]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[13]  Gérard G. Medioni,et al.  Corner detection and curve representation using cubic B-splines , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[14]  Radu Horaud,et al.  Finding Geometric and Relational Structures in an Image , 1990, ECCV.

[15]  James W. Cooper,et al.  Early jump-out corner detectors , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[16]  C. Tomasi.  Detection and Tracking of Point Features , 1991 .

[17]  Olaf Kübler,et al.  Simulation of neural contour mechanisms: from simple to end-stopped cells , 1992, Vision Research.

[18]  Aaron Heller,et al.  An experimental evaluation of projective invariants , 1992 .

[19]  R. Deriche.  Recursively Implementing the Gaussian and its Derivatives , 1993 .

[20]  Rachid Deriche,et al.  Recovering and characterizing image features using an efficient model based approach , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Max A. Viergever,et al.  Higher Order Differential Structure of Images , 1993, IPMI.

[22]  Wolfgang Förstner,et al.  A Framework for Low Level Feature Extraction , 1994, ECCV.

[23]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[24]  Roger Mohr,et al.  Accuracy in image measure , 1994, Other Conferences.

[25]  Its'hak Dinstein,et al.  Using Simple Decomposition for Smoothing and Feature Point Detection of Noisy Digital Curves , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Deformable Kernels for Early Vision , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Rachid Deriche,et al.  A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry , 1995, Artif. Intell..

[28]  Karl Rohr,et al.  Evaluation of corner extraction schemes using invariance methods , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[29]  Michael Werman,et al.  Ridge's corner detection and correspondence , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[30]  Sudeep Sarkar,et al.  Robust Visual Method for Assessing the Relative Performance of Edge-Detection Algorithms , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Didier Demigny,et al.  A Discrete Expression of Canny's Criteria for Step Edge Detector Performances Evaluation , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Robert Laganière,et al.  Morphological corner detection , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[33]  Dmitry B. Goldgof,et al.  An Objective Comparison Methodology of Edge Detection Algorithms Using a Structure from Motion Task , 1998, CVPR.

[34]  Han Wang,et al.  Gray Level Corner Detection , 1998, MVA.

[35]  Farzin Mokhtarian,et al.  Robust Image Corner Detection Through Curvature Scale Space , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[36]  Laxmi Parida,et al.  Junctions: Detection, Classification, and Reconstruction , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  Sean Dougherty,et al.  Edge detector evaluation using empirical ROC curves , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[38]  Joan Serrat,et al.  Evaluation of Methods for Ridge and Valley Detection , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[39]  Kevin W. Bowyer,et al.  Comparison of Edge Detectors Using an Object Recognition Task , 1999, CVPR.

[40]  Shree K. Nayar,et al.  Global measures of coherence for edge detector evaluation , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[41]  Kevin W. Bowyer,et al.  Introduction to the Special Section on Empirical Evaluation of Computer Vision Algorithms , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[42]  J. Koenderink,et al.  Representation of local geometry in the visual system , 1987, Biological Cybernetics.

[43]  Stephen M. Smith,et al.  SUSAN—A New Approach to Low Level Image Processing , 1997, International Journal of Computer Vision.

[44]  Rachid Deriche,et al.  Using Canny's criteria to derive a recursively implemented optimal edge detector , 1987, International Journal of Computer Vision.

[45]  Karl Rohr,et al.  Recognizing corners by fitting parametric models , 1992, International Journal of Computer Vision.

[46]  Hiroshi Murase,et al.  Parametric Feature Detection , 1996, International Journal of Computer Vision.

[47]  Yehezkel Yeshurun,et al.  Context-free attentional operators: The generalized symmetry transform , 1995, International Journal of Computer Vision.

[48]  Rachid Deriche,et al.  A computational approach for corner and vertex detection , 1993, International Journal of Computer Vision.

[49]  Karl Rohr,et al.  Localization properties of direct corner detectors , 1994, Journal of Mathematical Imaging and Vision.