Partial shape similarity of contours is needed for object recognition

We will provide psychophysical evidence that recognition of parts of object contours is a necessary component of object recognition. It seems to be obvious that the recognition of parts of object contours is performed by applying a partial shape similarity measure to the query contour part and to the known contour parts. The recognition is completed once a sufficiently similar contour part is found in the database of known contour parts. We will derive necessary requirements for any partial shape similarity measure based on this scenario. We will show that existing shape similarity measures do not satisfy these requirements, and propose a new partial shape similarity measure.

[1]  Zygmunt Pizlo,et al.  Regularization model of human binocular vision , 2005, IS&T/SPIE Electronic Imaging.

[2]  David J. Field,et al.  Contour integration by the human visual system: Evidence for a local “association field” , 1993, Vision Research.

[3]  Qiang Wang,et al.  Partial elastic matching of time series , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

[4]  D. Donoho,et al.  Adaptive Multiscale Detection of Smooth Curves Embedded in a Background of Uniform Random Points , 2003 .

[5]  R. Watt.  Scanning from coarse to fine spatial scales in the human visual system after the onset of a stimulus. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[6]  S. Chiba,et al.  Dynamic programming algorithm optimization for spoken word recognition , 1978 .

[7]  William Grimson,et al.  Object recognition by computer - the role of geometric constraints , 1991 .

[8]  Ulrich Eckhardt,et al.  Shape descriptors for non-rigid shapes with a single closed contour , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[9]  Neil A. Macmillan,et al.  Detection Theory: A User's Guide , 1991 .

[10]  C. Gilbert,et al.  Improvement in visual sensitivity by changes in local context: Parallel studies in human observers and in V1 of alert monkeys , 1995, Neuron.

[11]  O. Reiser,et al.  Principles Of Gestalt Psychology , 1936 .

[12]  Longin Jan Latecki,et al.  Special issue: Shape Representation and Similarity for Image Databases , 2002, Pattern Recognit..

[13]  Zygmunt Pizlo,et al.  Binocular shape constancy from novel views: The role of a priori constraints , 2006, Perception & psychophysics.

[14]  Z Pizlo,et al.  Shape constancy from novel views , 1999, Perception & psychophysics.

[15]  Alex Pentland,et al.  Perceptual Organization and the Representation of Natural Form , 1986, Artif. Intell..

[16]  T. Shipley,et al.  PART-BASED REPRESENTATIONS OF VISUAL SHAPE AND IMPLICATIONS FOR VISUAL COGNITION , 2002 .

[17]  Martin A. Fischler,et al.  An optimization-based approach to the interpretation of single line drawings as 3D wire frames , 1992, International Journal of Computer Vision.

[18]  H. Barlow.  Vision Science: Photons to Phenomenology by Stephen E. Palmer , 2000, Trends in Cognitive Sciences.

[19]  Zygmunt Pizlo,et al.  A new look at binocular stereopsis , 2005, Vision Research.

[20]  W. Richards,et al.  Perception as Bayesian Inference , 2008 .

[21]  Charles A. Bouman,et al.  Multiple Resolution Segmentation of Textured Images , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Donald D. Hoffman,et al.  Salience of visual parts , 1997, Cognition.

[23]  Manish Singh,et al.  What change detection tells us about the visual representation of shape. , 2005, Journal of vision.

[24]  Dimitrios Gunopulos,et al.  Indexing Multidimensional Time-Series , 2004, The VLDB Journal.

[25]  Donald J. Berndt,et al.  Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.

[26]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[27]  Donald D. Hoffman,et al.  Part-Based Representations of Visual Shape and Implications for Visual Cognition , 2001 .

[28]  Mary A. Peterson,et al.  Organization, segregation and object recognition , 1999 .

[29]  B. Wandell.  Foundations of vision , 1995 .

[30]  Dimitrios Gunopulos,et al.  Finding Similar Time Series , 1997, PKDD.

[31]  Kaleem Siddiqi,et al.  Parts of Visual Form: Computational Aspects , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Ernst Mach,et al.  The analysis of sensations and the relation of the physical to the psychical , 1914, The Mathematical Gazette.

[33]  Longin Jan Latecki,et al.  Shape Similarity Measure Based on Correspondence of Visual Parts , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Luiz A. Costa,et al.  Determining the similarity of deformable shapes , 1995, Vision Research.

[35]  Thomas Marill,et al.  Emulating the human interpretation of line-drawings as three-dimensional objects , 1991, International Journal of Computer Vision.

[36]  A. Rosenfeld,et al.  An exponential pyramid model of the time-course of size processing , 1995, Vision Research.

[37]  Yaoda Xu,et al.  Early computation of part structure: Evidence from visual search , 2002, Perception & psychophysics.

[38]  A. Pentland.  Recognition by Parts , 1987 .

[39]  Jacob Feldman,et al.  Visual comparisons within and between object parts: evidence for a single-part superiority effect , 2003, Vision Research.

[40]  David Mumford,et al.  Pattern Theory: the Mathematics of Perception , 2002, math/0212400.

[41]  M. Healy,et al.  Missing Values in Experiments Analysed on Automatic Computers , 1956 .

[42]  J. Hochberg,et al.  Pictorial recognition as an unlearned ability: a study of one child's performance. , 1962, The American journal of psychology.

[43]  Tomaso Poggio,et al.  Computational vision and regularization theory , 1985, Nature.

[44]  Nicolai Petkov,et al.  Distance sets for shape filters and shape recognition , 2003, IEEE Trans. Image Process..

[45]  I. Biederman,et al.  Recognizing depth-rotated objects: Evidence and conditions for three-dimensional viewpoint invariance. , 1993 .

[46]  Corinna Cortes,et al.  Boosting Decision Trees , 1995, NIPS.

[47]  Dave Regan,et al.  Human perception of objects: early visual processing of spatial form defined by luminance , 2000 .

[48]  C. Tyler.  Human Symmetry Perception and Its Computational Analysis , 2002 .

[49]  Steven J. Karau,et al.  Social Loafing: Research Findings^ Implications^ and Future Directions , 2022 .

[50]  Rodney A. Brooks,et al.  Symbolic Reasoning Among 3-D Models and 2-D Images , 1981, Artif. Intell..

[51]  A. Rosenfeld,et al.  Curve Detection in a Noisy Image , 1997, Vision Research.

[52]  Azriel Rosenfeld,et al.  3-D Shape Recovery Using Distributed Aspect Matching , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[53]  S. Coren,et al.  Principles of perceptual organization and spatial distortion: the gestalt illusions. , 1980, Journal of experimental psychology. Human perception and performance.

[54]  Jon Driver,et al.  Parallel computation of symmetry but not repetition within single visual shapes , 1994 .

[55]  A. Treisman.  Perceptual grouping and attention in visual search for features and for objects. , 1982, Journal of experimental psychology. Human perception and performance.

[56]  Zygmunt Pizlo,et al.  3-D shape perception , 1995, Perception & psychophysics.

[57]  I. Biederman.  Human image understanding: Recent research and a theory , 1985, Computer Vision Graphics and Image Processing.

[58]  D. Mumford.  Pattern theory: a unifying perspective , 1996 .

[59]  Longin Jan Latecki,et al.  Convexity Rule for Shape Decomposition Based on Discrete Contour Evolution , 1999, Comput. Vis. Image Underst..

[60]  Philip N. Klein,et al.  On Aligning Curves , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[61]  A. Joshi,et al.  The traveling salesman problem: A hierarchical model , 2000, Memory & cognition.

[62]  Jon Driver,et al.  Obligatory edge-assignment in vision: The role of figure and part segmentation in symmetry detection. , 1995 .

[63]  Luciano da Fontoura Costa,et al.  Shape Analysis and Classification: Theory and Practice , 2000 .