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In the context of tree species recognition, botanists knowledge was used in different works specially when recognising tree species through leaves. In this paper, two sub-classification strategies for tree species recognition are proposed. For each sub-classification strategy, Basic belief assignment (Bba) was determined and obtained data were fused thanks to a totally adaptive fusion system implemented...
Non-rigid point set registration is a fundamental problem for many computer vision technologies. In this paper, we proposed a new non-rigid point set registration method based on coherent spatial mapping (CSM) and local geometrical constraint. Our central idea is to express each point as a weighted sum of several nearest neighbors and the same relation holds after the transformation. The registration...
In this paper, we address the problem of shape part recognition. For this purpose, we define a robust distance between shape parts based on geodesics in the shape space. The proposed distance uses an elastic shape matching to handle elastic deformations and compare shape parts locally. This distance is applied to shape part classification and shape part retrieval. An experimental study through the...
3D Object recognition is one of the big problems in Computer Vision which has a direct impact in Robotics. There have been great advances in the last decade thanks to point cloud descriptors. These descriptors do very well at recognizing object instances in a wide variety of situations. Of great interest is also to know how descriptors perform in object classification tasks. With that idea in mind,...
The use of Millimetre wave images has been proposed recently in the biometric field to overcome certain limitations when using images acquired at visible frequencies. In this paper, several body shape-based techniques were applied to model the silhouette of images of people acquired at 94 GHz. We put forward several methods for the parameterization and classification stage with the objective of finding...
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...
The use of MMW images has been proposed recently in the biometric field aiming to overcome certain limitations when using images acquired at visible frequencies. In this paper, several body shape-based techniques are applied to model the silhouette of images of people acquired at 94 GHz. Three main approaches are presented: a baseline system based on the Euclidean distance, a dynamic programming method...
A critical step of on-line handwritten diagram recognition is the segmentation between text and symbols. It is still an open problem in several approaches of the literature. However, for a human operator, text/symbol segmentation is an easy task and does not even need understanding diagram semantics. It is done thanks to the use of both structural knowledge and statistical analysis. A human operator...
In this paper, we address a new scheme for symbol retrieval based on relation bag-of-features (BOFs) which are computed between the extracted visual primitives. Our feature consists of pair wise spatial relations from all possible combinations of individual visual primitives. The key characteristic of the overall process is to use topological information to guide directional relations. Consequently,...
In this paper we use the Earth Movers Distance (EMD) algorithm to measure similarity between shapes for recognizing and searching Arabic words. We have used the Shape Context and the Angular Radial Partitioning descriptors to evaluate matching and recognizing with EMD. Based on the encouraging results of high accuracy and recall, we follow the low-distortion embedding of the Earth Mover's Distance...
The outer ear has been established as a stable and unique biometric characteristic, especially in the field of forensic image analysis. In the last decade, increasing efforts have been made for building automated authentication systems utilizing the outer ear. One essential processing step in these systems is the detection of the ear region. Automated ear detection faces a number of challenges, such...
This paper introduces a vision-based motion capture system. Motion capturing technology consists of two categories: model-based tracking and example-based indexing. The motion capturing systems face two challenges: parameter estimation in high-dimensional space and self-occlusion. Our algorithm extends the locality sensitive hashing (LSH) method to find the approximate examples and then estimates...
The human cortex is a folded ribbon of neurons with a high inter-individual variability. It is a challenging structure to study especially when measuring small changes resulting from normal aging and neurodegenerative disorders such as Alzheimer's Disease (AD). Recent studies have proposed surface based approaches for statistical population comparison of cortical changes since such approaches better...
A new text recognition algorithm is proposed based on Shape Context and Fuzzy inference to solve the corresponding problems. And the algorithm is used to improve accuracy and effectiveness of recognition. Then experiments results show that our proposed method is effective.
In this paper, an efficient 2D shape matching algorithm is proposed. The proposed algorithm uses the mean distances and standard deviations of shape contexts as the index of shapes to reduce the search space of the previous work on shape matching with shape context descriptor. The best-fit ellipse modeling is adopted as the preprocessing for normalizing its scale. The simulation databases include...
Shape matching is a very critical problem in computer vision, and many smart features have been designed in recent literature for improving the similarity measure between pairs of shapes, and most of them consider either distribution of the sample contour points, or convexity/concavity property of the contour. In this paper, we design a novel shape feature to capture the Co-Occurrence Pattern (COP)...
This paper describes an efficient approach for the problem of shape modeling and classification. It is shown that this problem can be approached within a hybrid generative discriminative framework that integrates both finite mixture models and support vectors machines (SVM). The proposed framework is based on the generation of Fisher SVM kernel from the multinomial Beta-Liouville finite mixture model...
We propose a new method for shape recognition and retrieval based on dynamic programming. Our approach uses the dynamic programming algorithm to compute the optimal score and to find the optimal alignment between two strings. First, each contour of shape is represented by a set of points. After alignment and matching between two shapes, the contours are transformed into a string of symbols and numbers...
This paper presents a novel scheme for object completion in a video. The framework includes three steps: posture synthesis, graphical model construction, and action prediction. In the very beginning, a posture synthesis method is adopted to enrich the number of postures. Then, all postures are used to build a graphical model of object action which can provide possible motion tendency. We define two...
Two-dimensional shape matching is a fundamental problem in pattern recognition and computer vision. A challenging aspect of this problem is to find a distinctive shape descriptor which is able to handle common geometric transformations, occlusions and deformations. In this paper, we present a novel and distinctive shape descriptor based on shape distributions. The key concept of our method is that...
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