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In this paper, we present a method to improve a robot's imitation performance in a drawing scenario by inserting pauses in motion. Human's drawing skills are said to develop through five stages: 1) Scribbling, 2) Fortuitous Realism, 3) Failed Realism, 4) Intellectual Realism, and 5) Visual Realism. We focus on stages 1) and 3) for creating our system, each corresponding to body babbling and imitation...
In this paper, a complete logo detection/ recognition system for document images is proposed. In the proposed system, first, a logo detection method is employed to detect a few regions of interest (logo-patches), which likely contain the logo(s), in a document image. The detection method is based on the piece-wise painting algorithm (PPA) and some probability features along with a decision tree. For...
Effective information retrieval on handwritten documentimages has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each...
In this work we present a handwritten word spotting approach that takes advantage of the a priori known order of appearance of the query words. Given an ordered sequence of query word instances, the proposed approach performs a sequence alignment with the words in the target collection. Although the alignment is quite sparse, i.e. the number of words in the database is higher than the query set, the...
This paper presents a Document Image Analysis (DIA) system able to extract homogeneous typed and handwritten text regions from complex layout documents of various types. The method is based on two connected component classification stages that successively discriminate text/non text and typed/handwritten shapes, followed by an original block segmentation method based on white rectangles detection...
In this paper, we address the problem of recognizing human actions from videos. Human actions recognition is a challenging task in computer vision. We propose a method to solve this problem using Longest Common Sub-Sequence (LCSS) algorithm and Shape Context (SC). Our contributions in this paper are twofold. First, we show the applicability of the SC as a pairwise shape-similarity measurement for...
Spectral methods have been extensively studied for point pattern matching. In this work, we aim to render the spectral matching algorithm more robust for positional jitter and outliers. We concentrate on the issue of spectral representation for point patterns. A local structural descriptor, called the line graph spectral context, is proposed to characterize the attribute of point patterns, making...
In this paper, we propose a noise removal approach that significantly improves the performance of sophisticated shape matching techniques. Existing shape matching techniques focus on complex algorithms without giving much consideration to the noise removing preprocessing techniques. These preprocessing techniques can reasonably improve the accuracy where the shapes are affected by cracks. We present...
In this paper we report our study on improving hand pose estimation using support vector machines with evolutionary procedure for selecting the training set. There are many various approaches to extract and classify hand shape features, including histograms of oriented gradients, Hausdorff distances or shape contexts. Here, we explore how to exploit support vector machines to recognize a hand pose...
Traffic Sign Recognition is nowadays widely used in the automobile industry, it provides a good solution for driver assistance systems, it can alert the driver and control or prohibit certain actions, and this can significantly increase driving safety and comfort. This paper presents a study to design, implement and test a method of detecting traffic signs, based on computer vision. The system implemented...
Double Patterning Technology (DPT) conflicts express themselves as odd cycles of spacing between layout shapes. One way of resolving these is by imposing a large spacing constraint between a pair of shapes participant in an odd cycle. However, this may shrink spacing in other parts of the layout and introduce DRC violations or new DPT conflicts. In this work, we model DPT conflict resolution as a...
In a context where healthcare costs are increasing exponentially worldwide, both developed and developing countries and making e-health a priority. However, reducing the disparity in healthcare quality and delivery by way of pervasive e-health solutions remains elusive. At least in part, this is attributed to the inherent complexity that characterizes modern healthcare environments. In order to improve...
Online advertising strategies for health care services remain under-investigated in spite of the current popularity of these services. Due to the industry characteristics and legal regulations towards medical services in many countries, hospitals and clinics ignored advertising planning for decades. Today, not only the environment but also medical products have changed. With the enhanced living standards,...
The lack of a competent design theory to shape information system security policy and implementation has exacerbated an already troubling lack of security. Information systems remain insecure and therefore untrustworthy even after more than half a century of technological evolution. The issues grow ever more severe as the volume of data grows exponentially and the cloud emerges as a preferred repository...
This exploratory paper answers questions about how Facebook as a game platform influences players' game play, arguing that platforms can shape play as well as cheating behaviors in important ways. It is based on a survey of players of social network games, exploring their attitudes towards cheating in games such as The Sims Social and City Ville. It also includes results from follow-up qualitative...
A method for partial near-duplicate retrieval in random images is proposed and evaluated. Unlike the majority of existing methods, it is based on matching individual keypoints only (i.e. no analysis/verification of configuration constraints). The proposed description of keypoints incorporates affine-invariant representation of keypoint bundles (photometric and geometric properties of neighboring keypoints)...
In this paper, we propose a new method for cartoon image retrieval based on the local invariant shape feature, named Scalable Shape Context. The proposed feature uses the Harris-Lap lace corner to localize the key points and corresponding scale in the cartoon image. Then, we use Shape Context to describe the local shape. The feature point matching is achieved by a weighted bipartite graph matching...
Map matching is a fundamental task in many robot vision applications, including viewpoint localization, change detection, alignment, merging, segmentation of maps, and multi-robot mapping. Existing frameworks so far have concentrated on local feature-based approach, where discriminative local features are extracted from the maps and visual indexing and map database searched are performed to find correspondence...
In this study, a global shape descriptor that we call Mixture of Poses (MoP) is proposed to solve human behavior understanding problem. Firstly, the Shape Context Descriptor (SCD) is obtained for each frame. SCD is a low level feature representing a single pose, that is the shape at a single frame. PCA is used for data reduction while obtaining SCDs. The collection of SCDs obtained in a video of a...
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