Search results for "3D pose estimation"

showing 4 items of 4 documents

FastSLAM 2.0: Least-Squares Approach

2006

In this paper, we present a set of robust and efficient algorithms with O(N) cost for the following situations: object detection with a laser ranger; mobile robot pose estimation and a FastSLAM improved implementation. Objected detection is mainly based on a novel multiple line fitting method, related with walls at the environment. This method assumes that walls at the environment constitute a regular constrained angles. A line-based pose estimation method is also proposed, based on Least-Squares (LS). This method performs the matching of detected lines and estimated map lines and it can provide the global pose estimation under assumption of known Data-Association. FastSLAM 1.0 has been imp…

Extended Kalman filterLine fittingComputer sciencebusiness.industryLine (geometry)Mobile robotComputer visionArtificial intelligencebusiness3D pose estimationPoseLeast squaresObject detection2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
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Real-Time Human Pose Estimation from Body-Scanned Point Clouds

2015

International audience; This paper presents a novel approach to estimate the human pose from a body-scanned point cloud. To do so, a predefined skeleton model is first initialized according to both the skeleton base point and its torso limb obtained by Principal Component Analysis (PCA). Then, the body parts are iteratively clustered and the skeleton limb fitting is performed, based on Expectation Maximization (EM). The human pose is given by the location of each skeletal node in the fitted skeleton model. Experimental results show the ability of the method to estimate the human pose from multiple point cloud video sequences representing the external surface of a scanned human body; being r…

Computer sciencebusiness.industryHuman pose estimationPoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]TorsoMissing data3D pose estimation[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]medicine.anatomical_structure[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Expectation–maximization algorithmPrincipal component analysismedicineComputer visionPoint (geometry)Artificial intelligencebusinessskeleton modelPoseComputingMethodologies_COMPUTERGRAPHICSpoint cloud
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Object Recognition and Modeling Using SIFT Features

2013

In this paper we present a technique for object recognition and modelling based on local image features matching. Given a complete set of views of an object the goal of our technique is the recognition of the same object in an image of a cluttered environment containing the object and an estimate of its pose. The method is based on visual modeling of objects from a multi-view representation of the object to recognize. The first step consists of creating object model, selecting a subset of the available views using SIFT descriptors to evaluate image similarity and relevance. The selected views are then assumed as the model of the object and we show that they can effectively be used to visual…

Object RecognitionSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSIFT.business.industryComputer science3D single-object recognitionObject Recognition; Pose Estimation; Object Model; SIFT.ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognition3D pose estimationObject (computer science)Object-oriented designPose EstimationHaar-like featuresObject modelViola–Jones object detection frameworkComputer visionArtificial intelligencebusinessPoseObject Model
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Head Pose Estimation for Sign Language Video

2013

We address the problem of estimating three head pose angles in sign language video using the Pointing04 data set as training data. The proposed model employs facial landmark points and Support Vector Regression learned from the training set to identify yaw and pitch angles independently. A simple geometric approach is used for the roll angle. As a novel development, we propose to use the detected skin tone areas within the face bounding box as additional features for head pose estimation. The accuracy level of the estimators we obtain compares favorably with published results on the same data, but the smaller number of pose angles in our setup may explain some of the observed advantage.

business.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSign language3D pose estimationMotion captureData setSupport vector machineMinimum bounding boxFace (geometry)Computer visionArtificial intelligencebusinessPose
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