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This paper presents a new method for writer identification, which emulates the approach taken by forensic document examiners. It combines a novel feature, which uses contour gradients to capture local shape and curvature, with character segmentation to create a pseudo-alphabet for a given handwriting sample. A distance metric is then defined between elements of these alphabets that captures character...
Handwriting recognition is the ability of a computer to receive and interpret intelligible handwritten input. Recognition systems are divided into two categories: holistic approach and analytical approach. A holistic approach handles the whole input image, while analytical approach involves two steps namely; segmentation and combination. Handwriting recognition began long time ago mainly in Latin...
Human action recognition has been attracted lots of interest from computer vision researchers due to its various promising applications. In this paper, we employ Pyramid Histogram of Orientation Gradient (PHOG) to characterize human figures for action recognition. Comparing to silhouette-based features, the PHOG descriptor does not require extraction of human silhouettes or contours. Two state-space...
Determining identity of a person is a continually growing subfield of computational intelligence. Measurable biological characteristics, or biometrics, are used to quantify the physical features of an individual for use as a means of identification. There have been psychological studies recently that suggest a new biometric - facial dynamics. In this work, the hypothesis is that facial dynamics of...
Online handwriting recognition of Indian scripts has been drawing increasing attention in recent years. Related research has gained further momentum due to recent planned funding by the Govt. of India towards technology development of Indian languages and scripts. Standard databases of handwritten characters of a few Indian scripts have already become available. These include online handwritten character...
This paper presents a method to recognize human actions from sequences of depth maps. Specifically, we employ an action graph to model explicitly the dynamics of the actions and a bag of 3D points to characterize a set of salient postures that correspond to the nodes in the action graph. In addition, we propose a simple, but effective projection based sampling scheme to sample the bag of 3D points...
Graphical models have been shown to provide a natural framework for modelling high level action transition constraints, and to simultaneously segment and recognize a sequence of actions. Spatio-temporal interest points (STIPs) have been proposed as suitable features for action detection. These interest points are typically mapped to a set of codewords, and actions are detected by accumulating the...
In this paper, we introduce a shape-based, time-scale invariant feature descriptor for 1-D sensor signals. The timescale invariance of the feature allows us to use feature from one training event to describe events of the same semantic class which may take place over varying time scales such as walking slow and walking fast. Therefore it requires less training set. The descriptor takes advantage of...
In sign language, hand positions and movements represent meaning of words. Hence, we have been developing sign language recognition methods using both of hand positions and movements. However, in the previous studies, each feature has same weight to calculate the probability for the recognition. In this study, we propose a sign language recognition method by using a multi-stream HMM technique to show...
In this paper, we present an approach for detecting MTV video shot using Hidden Markov Models (HMMs), in which the color, shape and motion features are utilized. First, the temporal characteristics of different shot transitions are exploited and an HMM is constructed for shot transitions, including cut and gradual transitions. Secondly, a trained HMM are used to recognize the shot transition automatically,...
Compared with some "static" biometrics such as human face and fingerprint, person authentication based on lip movement has the advantage of incorporating "dynamic" features which contain rich information indicating the speaker identity. This paper proposes a new lip feature representation and analyzes its discrimination power for person authentication. Since the original lip features...
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