Search results for "Computer Vision and Pattern Recognition"
showing 10 items of 997 documents
Photometric Gaussian Mixtures for Direct Virtual Visual Servoing of Omnidirectional Camera
2021
International audience
Multi-Scale Feature Extraction for Vehicle Detection Using Phis-Lbp
2018
International audience; Multi-resolutionobjectdetectionfacesseveraldrawbacksincludingitshighdimensionalityproducedby a richer image representation in different channels or scales. In this paper, we propose a robust and lightweight multi-resolution method for vehicle detection using local binary patterns (LBP) as channel feature. Algorithm acceleration is done using LBP histograms instead of multi-scale feature maps and by extrapolating nearby scales to avoid computing each scale. We produce a feature descriptor capable of reaching a similar precision to other computationally more complex algorithms but reducing its size from 10 to 800 times. Finally, experiments show that our method can obt…
Towards automated and operational forest inventories with T-Lidar
2011
International audience; Forest inventory automation has become a major issue in forestry. The complexity of the segmentation of 3D point cloud is due to mutual occlusion between trees, other vegetation, or branches. That is why, the applications done until now are limited to the estimation of the DBH (Diameter at Breast Height), the tree height and density estimation. Furthermore other parameters could also be detected, such as volume or species of trees (Reulke and Haala) . . . This paper presents an effective approach for automatic detection, isolation of trees and DBH estimation. Tree isolation is achieved using an innovative approach based on a clustering methodology followed by a skele…
A Framework for Mesh Segmentation and Annotation using Ontologies
2015
International audience; Mesh segmentation and annotation using semantics has received an increased interest with the recent democratisation of 3D reconstruction methods. The common approach is to perform this task in two steps, by first segmenting the mesh and then annotating it. However, this approach does not allow one part to take advantage of the other. In image processing, some methods are combining segmentation and annotation, but they are not generic and require implementation adjustments or rewritings for each modification of the expert knowledge. In this work, we describe an original framework that mixes segmen-tation and annotation while minimizing the required geometric analysis …
SHREC'12 Track: 3D mesh segmentation
2012
International audience; 3D mesh segmentation is a fundamental process in many applications such as shape retrieval, compression, deformation, etc. The objective of this track is to evaluate the performance of recent segmentation methods using a ground-truth corpus and an accurate similarity metric. The ground-truth corpus is composed of 28 watertight models, grouped in five classes (animal, furniture, hand, human and bust) and each associated with 4 ground-truth segmentations done by human subjects. 3 research groups have participated to this track, the accuracy of their segmentation algorithms have been evaluated and compared with 4 other state-of-the-art methods.
Convergence Analysis of Distributed Set-Valued Information Systems
2016
This paper focuses on the convergence of information in distributed systems of agents communicating over a network. The information on which the convergence is sought is not rep- resented by real numbers, as often in the literature, rather by sets. The dynamics of the evolution of information across the net- work is accordingly described by set-valued iterative maps. While the study of convergence of set-valued iterative maps is highly complex in general, this paper focuses on Boolean maps, which are comprised of arbitrary combinations of unions, intersections, and complements of sets. For these important class of systems, we provide tools to study both global and local convergence. A distr…
Learning-based multiresolution transforms with application to image compression
2013
In Harten's framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact and predicted values. In this paper we use tools of statistical learning in order to design a more accurate prediction operator in this framework based on a training sample, resulting in multiresolution decompositions with enhanced sparsity. In the case of images, we incorporate edge detection techniques in the design of the prediction operator in order to avoid Gibbs phenomenon. Numerical tests are presented showing that the …
Parallel distance transforms on pyramid machines: Theory and implementation
1990
Abstract A distance transform of a binary image is an array each of whose elements gives the distance from the corresponding pixel to the closest ‘1’ in the binary image. Distance transforms have uses in image matching and shape analysis, among other applications. We present a parallel algorithm for weighted distance transforms that runs particularly efficiently on hierarchical cellular-logic machines, a subclass of the architectures known as pyramid machines. The algorithm computes the 3–4 distance transform; however it can be readily adapted to the city-block (‘Manhattan’) and chessboard distance measures. The algorithm runs in O(M) time, for an M × M image. Since it avoids using arithmet…
Automating statistical diagrammatic representations with data characterization
2017
The search for an efficient method to enhance data cognition is especially important when managing data from multidimensional databases. Open data policies have dramatically increased not only the volume of data available to the public, but also the need to automate the translation of data into efficient graphical representations. Graphic automation involves producing an algorithm that necessarily contains inputs derived from the type of data. A set of rules are then applied to combine the input variables and produce a graphical representation. Automated systems, however, fail to provide an efficient graphical representation because they only consider either a one-dimensional characterizat…
A reconfigurable architecture for autonomous visual-navigation
2003
This paper describes the design of a reconfigurable architecture for implementing image processing algorithms. This architecture is a pipeline of small identical processing elements that contain a programmable logic device (FPGA) and double port memories. This processing system has been adapted to accelerate the computation of differential algorithms. The log-polar vision selectively reduces the amount of data to be processed and simplifies several vision algorithms, making possible their implementation using few hard-ware resources. The reconfigurable architecture design has been devoted to implementation, and has been employed in an autonomous platform, which has power consumption, size a…