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3D model based approach for face recognition has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper we propose a novel 3D face representation algorithm based on pixel to vertex map (PVM)...
Inspired by the work on sensory substitution which shows the technical and practical possibilities for perceptual learning, we have carried out a global longitudinal study of the learning capacities for reading digital graphical objects by four blind high-school students. We report here the results obtained with the Tactos system during certain phases of this study, in particular the acquisition of...
This paper proposes a novel face detection method that finds tiny faces located at a long range even with low-resolution input images captured by a moving robot. The proposed approach can locate extremely small-sized face regions of 12x12 pixels by combining the results from mean-shift color tracking, short- and long-range face detection, and omega shape detection. According to the experimental results...
This paper presents a novel and effective method of shape analysis and recognition based on skeleton and morphological structure. A series of preprocessing algorithms, smooth following and liberalization are introduced, and series of morphological structural points of image contour are extracted and merged. A series of basic shapes and a main shape of object image are described and segmented based...
This paper presents an algorithm to capture outline of bitmap characters. In order to obtain outline, a cubic function with one shape parameter is used. Genetic algorithm is applied to find the value of shape parameter. The procedure of capturing outline consists of the steps: boundary detection, detection of corner points, break points and fitting the curve.
Graph matching is a fundamental problem with many applications in computer vision. Patterns are represented by graphs and pattern recognition corresponds to finding a correspondence between vertices from different graphs. In many cases, the problem can be formulated as a quadratic assignment problem, where the cost function consists of two components: a linear term representing the vertex compatibility...
Content-based image retrieval relies on the use of efficient and effective image descriptors. One of the most important components of an image descriptor is concerned with the distance function used to measure how similar two images are. This paper presents a clustering approach based on distances correlation for computing the similarity among images. Conducted experiments involving shape, color,...
This article presents a partial matching approach based on set exclusion criteria applied to livestock brand retrieval. A set exclusion measure function, depending on local shape features, is formulated. This exclusion measure helps to determine if a registered brand is a subset of another existing brand, or vice-versa. Local features are obtained taking account the relative spatial distribution of...
We propose a method for human activity recognition in videos, based on shape analysis. We define local shape descriptors for interest points on the detected contour of the human action and build an action descriptor using a Bag of Features method. We also use the temporal relation among matching interest points across successive video frames. Further, an SVM is trained on these action descriptors...
A common approach to human action recognition is to use 2-D silhouettes in the space-time volume as a basis for further extraction of useful features. In this paper, we present a novel motion representation based on difference images. We show that this representation exploits the dynamics of motion, and show its effectiveness in action recognition. Moreover, experimental results demonstrate that this...
Bone mineral density (BMD) measurements and fracture analysis of the spine bones are restricted to the Vertebral bodies (VBs). In this paper, we propose a novel 3D shape based method to segment VBs in clinical computed tomography (CT) images without any user intervention. The proposed method depends on both image appearance and shape information. 3D shape information is obtained from a set of training...
We investigate the problem of facial expression recognition using 3D face data. Our approach is based on local shape analysis of several relevant regions of a given face scan. These regions or patches from facial surfaces are extracted and represented by sets of closed curves. A Riemannian framework is used to derive the shape analysis of the extracted patches. The applied framework permits to calculate...
In this paper, we present a robust framework for action recognition in video, that is able to perform competitively against the state-of-the-art methods, yet does not rely on sophisticated background subtraction preprocess to remove background features. In particular, we extend the Implicit Shape Modeling (ISM) of [10] for object recognition to 3D to integrate local spatiotemporal features, which...
In this paper we provide a framework of detection and localization of multiple similar shapes or object instances from an image based on shape matching. There are three challenges about the problem. The first is the basic shape matching problem about how to find the correspondence and transformation between two shapes; second how to match shapes under occlusion; and last how to recognize and locate...
An endoscope is a medical instrument that acquires images inside the human body. An endoscope carries its own light source. Classic shape-from-shading can be used to recover the 3-D shape of objects in view. Recent implementations have used the Fast Marching Method (FMM). Previous FMM approaches recover 3-D shape under assumptions of parallel light source illumination and orthographic projection....
In this paper, we investigate the task of human action detection in crowded videos. Different from action analysis in clean scenes, action detection in crowded environments is difficult due to the cluttered backgrounds, high densities of people and partial occlusions. This paper proposes a method for action detection based on masks. No human segmentation or tracking technique is required. To cope...
We present a framework to classify small freeform objects in 3D aerial scans of a large urban area. The system first identifies large structures such as the ground surface and roofs of buildings densely built in the scene, by fitting planar patches and grouping adjacent patches similar in pose together. Then, it segments initial object candidates which represent the visible surface of an object using...
We propose an automatic deformation-driven correspondence algorithm for 3D point sets of non-rigid articulated shapes. Our approach uses simple geometric cages to embed the point set data and extract and match a coarse set of prominent features. We seek feature correspondences which lead to low-distortion deformations of the cages while satisfying the feature pairing. Our approach operates on the...
A novel 3D shape matching method is proposed in this paper. We first extract angular and distance feature pairs from pre-processed 3D models, then estimate their kernel densities after quantifying the feature pairs into a fixed number of bins. During 3D matching, we adopt the KL-divergence as a distance of 3D comparison. Experimental results show that our method is effective to match similar 3D shapes,...
Indexing into large database systems is essential for a number of applications. This paper presents a new indexing structure, which overcomes an important restriction of a previous indexing technique using a recently developed theorem from the domain of matrix analysis. Specifically, given a set of distance values computed by distance function, which do not necessarily satisfy the triangle inequality,...
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