Multiresolution spatial partitioning for shape representation

Bimbo, A. Del

doi:10.1109/icpr.2004.1334373

Cited by 6 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…, ( 2 ) of the lth order is defined on the corresponding repre sentations A l and of the form (1) for l = 0, …, L. Measure (2) allows one to introduce a sphere of the lth level as the following set of the objects…”

Section: Basic Terms and Model Of Classifiermentioning

confidence: 99%

“…One of the first approaches to constructing structural descriptions of geometric 2D shapes based on their hierarchical decomposition was suggested in [1]. In [2], a recursive decomposition method was used to construct the multiresolution rep resentations of 2D shapes by the tree structured sets of the shape spectral characteristics. In [3], some proce dures of matching hierarchically structured features were studied for shape recognition.…”

Section: Introductionmentioning

confidence: 99%

“…In [3], some proce dures of matching hierarchically structured features were studied for shape recognition. The approaches and methods considered in [1][2][3] allow one to con struct and compare effective descriptions of 2D objects given by the binary images. The structure of these descriptions is convenient for reducing calcula tions in procedures for processing hierarchically struc tured data; moreover, it enables one to apply fast algo rithms for analysis of 2D geometric shapes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Metric classifier using multilevel network of templates

Ganebnykh

Lange

Степанов³

2012

Pattern Recognit. Image Anal.

View full text Add to dashboard Cite

A new approach is proposed to constructing a classifier of two dimensional (2D) objects in a space of multiresolution object representations. The approach is based on constructing tree structured covers (TSCs) of clusters of a training set by spheres in the space of the object representations taken at the maximum resolution level. The covering spheres and their projections of all resolution levels generate a multilevel net work of templates in which the sphere centers yield the templates, while the spheres themselves form the influence regions of the templates at the corresponding resolution levels. Using the multilevel structure of the template network, a hierarchical search algorithm is proposed for making a decision group of the templates by a given voting criterion. A computational complexity of this algorithm is evaluated. An efficiency of the proposed TSC classifier is demonstrated by estimates of error rates in experiments on signature, hand gesture and face recognition, as well as by the comparative error rates obtained for these sources using the known SVM classifier.

show abstract

Section: Basic Terms and Model Of Classifiermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Metric classifier using multilevel network of templates

Ganebnykh

Lange

Степанов³

2012

Pattern Recognit. Image Anal.

View full text Add to dashboard Cite

show abstract

“…Design of the feature extraction function F v is an important and on-going research topic (10), (11) . Since our feature vector must be robust to illumination changes, HSV (Hue, Saturation, intensity Value) color representation is used in our system.…”

Section: Problemmentioning

confidence: 99%

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

Hirayama

Okada

Kondo

2006

JSME Int. J., Ser. C

View full text Add to dashboard Cite

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot's image database would be very useful. The main difference of the robot's image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.

show abstract

Moment-Based Pattern Representation Using Shape and Grayscale Features

Lange

Ganebnykh

Lange

Pattern Recognition and Image Analysis

View full text Add to dashboard Cite

Multiresolution spatial partitioning for shape representation

Cited by 6 publications

References 6 publications

Metric classifier using multilevel network of templates

Metric classifier using multilevel network of templates

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

Moment-Based Pattern Representation Using Shape and Grayscale Features

Contact Info

Product

Resources

About