We propose Fast Eigen Matching, a method for accelerating the matching and learning processes of the eigenspace method for rotation invariant template matching (RITM). Correlation-based template matching is one of the basic techniques used in computer vision. Among them, rotation invariant template matching (RITM), which locates a known template in a query irrespective of the template’s transla...

Object instance detection finds where a specific object instance is in an image or a video frame. It is a variation of object detection, but distinguished on two points. First, object detection focused on a category of object, while object instance detection focused on a specific object. For instance, object detection may work to find where toothpaste is in an image, while object instance detec...

Template matching is one of the most prevalent pattern recognition methods worldwide. It has found uses in most visual concept detection fields. In this work, we investigate methods for improving template matching by adjusting the weights of different regions of the template. We compare several weight maps and test the methods using the FERET face test set in the context of human eye detection.

We consider the template matching problem, in which one wants to find all good enough occurrences of a pattern template P from a larger image I . The current standard of template matching is based on cross correlation computed in Fourier domain, using the Fast Fourier Transform (FFT). This can be extended to rotations of the template by a suitable rotational sampling of the template. An alterna...

Object Recognition is inherently a hard problem in computer vision. Current standard object recognition techniques require small training data sets of images and apply sophisticated algorithms. These methods tend to perform poorly because the small data set does not reflect the true distribution (selection bias). Recently, Torralba et al [1] have proposed to develop a large data set of images (...

One of the most popular methods to extract useful informations from an image sequence is the template matching approach. In this well known method the tracking of a certain feature or target over time is based on the comparison of the content of each image with a sample template. In this article, we propose a 3D template matching algorithm that is able to track target corresponding to the proje...

One of the most popular methods to extract useful informations from an image sequence is the template matching approach. In this well known method the tracking of a certain feature or target over time is based on the comparison of the content of each image with a sample template. In this article, we propose an efficient robust template matching algorithm that is able to track targets in real ti...

This paper describes the employment of template matching principles for analysis of XML streams. We introduce TMPL, a template specification language, argue why it is better suited for stream analysis than conventional technologies, that are adopted to the requirements of data stream processing. We discuss the language’s constructs and their implications to runtime behaviour. Feasability of our...

Template matching is the search for a known object, represented by a template image, at an arbitrary location within a larger image. The local measure of match is often desired to be invariant to certain transforms, such as rotation and dilation, of the template. While a variety of solutions have been proposed, most are designed to provide invariance to a specific transform or set of transforms...