Recent studies show that small perturbations in video frames could misguide single object trackers. However, such attacks have been mainly designed for digital-domain videos (i.e., perturbation on full images), which makes them practically infeasible to evaluate the adversarial vulnerability of trackers real-world scenarios. Here we made first step towards physically feasible against visual tra...

Inter prediction is an important component for video coding which exploits the temporal correlation between frames and significantly reduces the redundancy in video sequences. In this paper, we propose a predictive patch matching for inter prediction based on template matching prediction. Besides the surrounding reconstructed pixels which form the template in template matching prediction, our p...

-Template matching is a fundamental technique of pattern recognition. Although this technique is very general, its applicability has been limited because of the difficulty often encountered when fitting templates to natural data. Natural patterns are often distorted, misshapen, stretched in size, fuzzy, rotated, translated, observed at an unusual perspective, etc. Flexible templates (rubber mas...

We present a learning-based, sliding window-style approach for the problem of detecting humans in still images. Instead of traditional concatenation-style image location-based feature encoding, a global descriptor more invariant to pose variation is introduced. Specifically, we propose a principled approach to learning and classifying human/non-human image patterns by simultaneously segmenting ...

A range of methodologies has been proposed to derive generalised forms of buildings at coarser scales. In this paper, we explore the use of simple pattern matching algorithms in order to select from a set of templates, a building outline that best characterises a more detailed form. This template matching process is used to simplify the form of rural buildings (farmsteads) in Danish mapping, an...

In this paper we present a novel approach which is combined local invariant feature descriptor named ARPIH (Angular Radial Partitioning Intensity Histogram) with histogram-based similar distance (HSD). The approach succeeds the ARPIH descriptor’s distinctive advantage and provides higher robustness in deformation image matching, such as rotation image, illumination changing image and perspectiv...

We consider the design principles of algorithms that match templates to images subject to spatiotemporal encoding. Both templates and images are encoded as temporal sequences of samplings from spatial patterns. Matching is required to be tolerant to various combinations of image perturbations. These include ones that can be modeled as parameterized uncertainties such as image blur, luminance, a...

We consider the design of a pattern recognition that matches templates to images, both of which are spatially sampled and encoded as temporal sequences. The image is subject to a combination of various perturbations. These include ones that can be modeled as parameterized uncertainties such as image blur, luminance, translation, and rotation as well as unmodeled ones. Biological and neural syst...

We present a novel template matching framework for detecting geometrically transformed objects. A template is a simplified representation of the object of interest by a set of pixel groups of any shape, and the similarity between the template and an image region is derived from the F-test statistic. The method selects a geometric transformation from a discrete set of transformations, giving the...

This paper presents a novel algorithm for detecting user-selected objects in given test images based on a new adaptive lifting scheme transform. Given an object as a template, we first select a set of coefficients as object features in the wavelet transform domain and then build an adaptive transform based on the selected features. The goal of the new adaptive transform is to vanish the selecte...