Contents 1. Introduction 1.1. Key ContributionsPublicationsOpen-Source Software

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Date: 2014-12-12 08:17:07 Computer vision Artificial intelligence Vision Robot control Image segmentation Pose Object detection Rigid motion segmentation British Machine Vision Conference		Contents 1. Introduction 1.1. Key ContributionsPublicationsOpen-Source Software Add to Reading List Source URL: hss.ulb.uni-bonn.de Download Document from Source Website File Size: 117,18 KB Share Document on Facebook

	Haptic SLAM: an ideal observer model for Bayesian inference of object shape and hand pose from contact dynamics Feryal M. P. Behbahani1 , Guillem Singla–Buxarrais2 and A. Aldo Faisal1,2,3 1 DocID: 1xTqR - View Document
	Ana Luisa Rébora’s Transfiguration of Figures The sense creates the pose. In this it moves and speaks. This is the figure and not An evading metaphor. DocID: 1vqc6 - View Document
	Sitting Positions from Easiest to Hardest (or from Better to Best) Easy Pose (Sukasana) Sit with both knees bent. Tuck your feet in front of your thighs so that the toes are pointing in opposite directions. Straighten y DocID: 1vq5M - View Document
	Human Pose Recovery and Behavior Analysis Group ChaLearn Looking at People 2015 new competitions: Age Estimation and Cultural Event Recognition Sergio Escalera, UB & CVC & ChaLearn DocID: 1vnzs - View Document
	Master Computer Vision & Artificial Intelligence Real-Time Hand Pose Recognition using Depth Sensors combined with Spherical Shape Model Descriptor Oscar Lopes DocID: 1vnp1 - View Document