3d geometric hashing using transform invariant features

Eskizara, Ömer
3D object recognition is performed by using geometric hashing where transformation and scale invariant 3D surface features are utilized. 3D features are extracted from object surfaces after a scale space search where size of each feature is also estimated. Scale space is constructed based on orientation invariant surface curvature values which classify each surface point's shape. Extracted features are grouped into triplets and orientation invariant descriptors are defined for each triplet. Each pose of each object is indexed in a hash table using these triplets. For scale invariance matching, cosine similarity is applied for scale variant triple variables. Tests were performed on Stuttgart database where 66 poses of 42 objects are stored in the hash table during training and 258 poses of 42 objects are used during testing. %90.97 recognition rate is achieved.


3D object recognition from range images using transform invariant object representation
AKAGÜNDÜZ, erdem; Ulusoy, İlkay (Institution of Engineering and Technology (IET), 2010-10-28)
3D object recognition is performed using a scale and orientation invariant feature extraction method and a scale and orientation invariant topological representation. 3D surfaces are represented by sparse, repeatable, informative and semantically meaningful 3D surface structures, which are called multiscale features. These features are extracted with their scale (metric size and resolution) using the classified scale-space of 3D surface curvatures. Triplets of these features are used to represent the surfac...
3D face reconstruction using stereo images and structured light
Öztürk, Ahmet Oğuz; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2007)
Nowadays, 3D modelling of objects from multiple images is a topic that has gained great recognition and is widely used in various fields. Recently, lots of progress has been made in identification of people using 3D face models, which are usually reconstructed from multiple face images. In this thesis, a system including stereo cameras and structured light is built for the purpose of 3D modelling. The system outputs are 3D shapes of the face and also the texture information registered to this shape. Althoug...
3D Object Recognition by Geometric Hashing
Eskizara, Omer; Akagündüz, Erdem; Ulusoy, İlkay (2009-01-01)
Using transform invariant 3D fatures obtained from a database of 3D range images, geometric hashing is applied for the purpose of 3D object recognition. Mean (H) and Gaussian (K) curvature values within a scale-space of the surface is used Since H and K values are used and a scale-space of the surface is constructed the method is independent of transformation and resolution. The method is tested on the Stuttgart 3D range image database [1].
A comparative study on polygonal mesh simplification algorithms
Yirci, Murat; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2008)
Polygonal meshes are a common way of representing 3D surface models in many different areas of computer graphics and geometry processing. However, these models are becoming more and more complex which increases the cost of processing these models. In order to reduce this cost, mesh simplification algorithms are developed. Another important property of a polygonal mesh model is that whether it is regular or not. Regular meshes have many advantages over the irregular ones in terms of memory requirements, effi...
3d face representation and recognition using spherical harmonics
Tunçer, Fahri; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2008)
In this study, a 3D face representation and recognition method based on spherical harmonics expansion is proposed. The input data to the method is range image of the face. This data is called 2.5 dimensional. Input faces are manually marked on the two eyes, nose and chin points. In two dimensions, using the marker points, the human face is modeled as two concentric half ellipses for the selection of region of interest. These marker points are also used in three dimensions to register the faces so that the n...
Citation Formats
Ö. Eskizara, “3d geometric hashing using transform invariant features,” M.S. - Master of Science, Middle East Technical University, 2009.