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The paper proposes an enhanced morphological contour/edge representation algorithm for the representation of 2D binary shapes of digital images. The concise representation algorithm uses representative lines of different sizes and types to cover all the significant features of the binary contour/edge image. These well-characterized representative line segments, which may overlap among different types,...
Developing efficient handwriting recognition systems that are fast and highly reliable is a challenging problem. This work represents the development of an online handwriting recognition system for Bangla script, widely used in eastern India and Bangladesh. In our approach, an online handwritten character/cluster is characterized by structure or shape based representation of a stroke in which a stroke...
The paper proposes a kind of joint feature with the geometric parameters and the color moment to represent the speaking-mouth image frames for the image-based visual speech synthesis system. The experiment results show the proposed joint feature can effectively provide the basis for classify the speaking-mouth images to distinguish the different speaking state according to the lip shape and the tooth...
In this paper, an improved temporal template called posture energy image (PEI) is proposed for human action representation and analysis. The template was computed from silhouette sequences which were generated from tracking and cutting moving regions in video clips. Comparing with other temporal templates, PEI is more intelligent: the time duration of PEI could be adjusted automatically. Experiments...
Active shape model (ASM) has been widely used to extract the facial features of a face image. In this paper, we propose an improved ASM algorithm for face image features extraction. The conventional ASM uses a single face model to represent a face, so it may not be able to capture the local shape variations effectively under different facial expressions. In our proposed approach, we use two individual...
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...
Human action analysis has recently received growing interest from vision researchers. In this paper, we present a simple but effective approach for action recognition by combining multiple complementary features with Gaussian process classification. Since it is often insufficient for a single type of feature derived from action videos to characterize variations among different motions, we propose...
In this paper, we present novel model to find the contour of an image in phases. The model was designed by modelling physical motion of a real elastic band. This is applied to top of any existing shape representation methods in order to offer additional information. The model makes us deal with global and local shape characteristics at once and results in robustness to distortion and noise on the...
3D moment invariants are traditionally based on region characteristics and the location of every pixel point, this will cause high calculation cost. In this paper, a novel shape representation named 3D gray level moment invariants is constructed. Some properties of the new representation including the independence of the translation, scaling and rotation transforms are proved. Experiments indicate...
The analytic signature is a recently proposed 2D shape representation scheme. It is tailored to the representation of shapes described by arbitrary sets of unlabeled points, or landmarks, because its most distinctive feature is the maximal invariance to a permutation of those points. The shape similarity of two point clouds can then be obtained from a direct comparison of their representations. However,...
Online contour-based tracking is considered through the estimation perspective. We propose a recursive dynamic filtering solution to the tracking problem. The state of the target is described by a pose state which represents the ensemble movement and a shape state which represents the local deformations. The shape state of the filter is described implicitly by a probability field with prediction and...
The active appearance model (AAM) has been shown powerful for modeling images of deformable objects. AAM uses principal component analysis (PCA) based linear subspaces to model the 2D shapes and textures of the images of a target object class. Such a representation allows AAM to represent a certain image very small number of parameters. A suitable constrained initialization is presented in matching...
Shape models (SMs), capturing the common features of a set of training shapes, represent a new incoming object based on its projection onto the corresponding model. Given a set of learned SMs representing different objects, and an image with a new shape, this work introduces a joint classification-segmentation framework with a twofold goal. First, to automatically select the SM that best represents...
Fourier descriptors (FD's) are widely used shape descriptors. By first warping the scanning speed of the contour before calculating the FD's, the shape approximation can be improved. This approach has never been properly tested on real applications. In this paper we compare these new shape descriptors to the regular FD's. A database of over 400 leaf shapes is approximated using these shape descriptors...
A new and fast method for dominant point detection and polygonal representation of a discrete curve is proposed. Starting from results of discrete geometry, the notion of maximal blurred segment of width v has been proposed, well adapted to possibly noisy and/or not connected curves. For a given width, the dominant points of a curve C are deduced from the sequence of maximal blurred segments of C...
A saliency-based target detection method for forward looking infrared (FLIR) image is proposed. Firstly, saliency map is computed using scale-space representation and separated into dark saliency map (DSM) and bright saliency map (BSM). Secondly, dark and bright regions of interest (ROI) are detected by respective type of saliency map using marker-based maximally stable extremal regions (MSER) detection...
A solution for identity and facial expression recognition is proposed using a two stage classifier approach using low dimensional representation of the geometry of the face. Face geometry is extracted from input images using Active Appearance Models (AAM) and low dimensional manifolds were then derived using Laplacian Eigen-Maps (LE) resulting in two types of manifolds, one for model identity and...
Supershape model is a recent primitive that represents numerous 3D shapes with several symmetry axes. The main interest of this model is its capability to reconstruct more complex shape than superquadric model with only one implicit equation. In this paper we propose a genetic algorithms to reconstruct a point cloud using those primitives. We used the pseudo-Euclidean distance to introduce a threshold...
Graph descriptor is usually focused on in computer vision for its flexibility and richness. However, in object recognition, it is difficult to catch the feature of an object completely with a straightforward way by a graph. In this paper, from a multiscale viewpoint, we propose a method to construct a vertex-labeled graph for image recognition where the label represents the importance of a vertex...
Scale space techniques have attracted much attention in the field of computer vision and image processing. In particular, the curvature scale space (CSS) technique was selected in the MPEG-7 standard due to a number of nice properties. In this paper the scale space concept is first explained in detail and its significance in solving shape-based vision problems is clarified. A brief survey of the theoretical...
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