Search results for "cognition."
showing 10 items of 7004 documents
Body Gestures and Spoken Sentences: A Novel Approach for Revealing User’s Emotions
2017
In the last decade, there has been a growing interest in emotion analysis research, which has been applied in several areas of computer science. Many authors have con- tributed to the development of emotion recognition algorithms, considering textual or non verbal data as input, such as facial expressions, gestures or, in the case of multi-modal emotion recognition, a combination of them. In this paper, we describe a method to detect emotions from gestures using the skeletal data obtained from Kinect-like devices as input, as well as a textual description of their meaning. The experimental results show that the correlation existing between body movements and spoken user sentence(s) can be u…
2D/3D Object Recognition and Categorization Approaches for Robotic Grasping
2017
International audience; Object categorization and manipulation are critical tasks for a robot to operate in the household environment. In this paper, we propose new methods for visual recognition and categorization. We describe 2D object database and 3D point clouds with 2D/3D local descriptors which we quantify with the k-means clustering algorithm for obtaining the Bag of Words (BOW). Moreover, we develop a new global descriptor called VFH-Color that combines the original version of Viewpoint Feature Histogram (VFH) descriptor with the color quantization histogram, thus adding the appearance information that improves the recognition rate. The acquired 2D and 3D features are used for train…
Visual tracking with omnidirectional cameras: an efficient approach
2011
International audience; An effective technique for applying visual tracking algorithms to omni- directional image sequences is presented. The method is based on a spherical image representation which allows taking into account the distortions and nonlinear resolution of omnidirectional images. Experimental results show that both deterministic and probabilistic tracking methods can effectively be adapted in order to robustly track an object with an omnidirectional camera.
3D Point Cloud Descriptor for Posture Recognition
2018
International audience
Automatic mass spectra recognition for Ultra High Vacuum systems using multilabel classification
2021
Abstract In Ultra High-Vacuum (UHV) systems it is common to find a mixture of many gases originating from surface outgassing, leaks and permeation that contaminate vacuum chambers and cause issues to reach ultimate pressures. The identification of these contaminants is, in general, done manually by trained technicians from the analysis of mass spectra. This task is time consuming and can lead to misinterpretation or partial understanding of issues. The challenge resides in the rapid identification of these contaminants by using some automatic gas identification technique. This paper explores the automatic and simultaneous identification of 80 molecules, including some of the most commonly p…
Static and Dynamic Objects Analysis as a 3D Vector Field
2017
International audience; In the context of scene modelling, understanding, and landmark-based robot navigation, the knowledge of static scene parts and moving objects with their motion behaviours plays a vital role. We present a complete framework to detect and extract the moving objects to reconstruct a high quality static map. For a moving 3D camera setup, we propose a novel 3D Flow Field Analysis approach which accurately detects the moving objects using only 3D point cloud information. Further, we introduce a Sparse Flow Clustering approach to effectively and robustly group the motion flow vectors. Experiments show that the proposed Flow Field Analysis algorithm and Sparse Flow Clusterin…
Simulation Goals and Metrics Identification
2016
Agent-Based Modeling and Simulation (ABMS) is a very useful means for producing high quality models during simulation studies. When ABMS is part of a methodological ap- proach it becomes important to have a method for identifying the objectives of the simulation study in a disciplined fashion. In this work we propose a set of guidelines for properly capturing and representing the goals of the simulations and the metrics, allowing and evaluating the achievement of a simulation objective. We take inspiration from the goal-question-metric approach and with the aid of a specific problem formalization we are able to derive the right questions for relating simulation goals and metrics.
Homography based egomotion estimation with a common direction
2017
International audience; In this paper, we explore the different minimal solutions for egomotion estimation of a camera based on homography knowing the gravity vector between calibrated images. These solutions depend on the prior knowledge about the reference plane used by the homography. We then demonstrate that the number of matched points can vary from two to three and that a direct closed-form solution or a Gröbner basis based solution can be derived according to this plane. Many experimental results on synthetic and real sequences in indoor and outdoor environments show the efficiency and the robustness of our approach compared to standard methods.
An Input Observer-Based Stiffness Estimation Approach for Flexible Robot Joints
2020
This letter addresses the stiffness estimation problem for flexible robot joints, driven by variable stiffness actuators in antagonistic setups. Due to the difficulties of achieving consistent production of these actuators and the time-varying nature of their internal flexible elements, which are subject to plastic deformation over time, it is currently a challenge to precisely determine the total flexibility torque applied to a robot's joint and the corresponding joint stiffness. Herein, by considering the flexibility torque acting on each motor as an unknown signal and building upon Unknown Input Observer theory, a solution for electrically-driven actuators is proposed, which consists of …
Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…