Toyota Jidosha Kabushiki Kaisha

Albert-ludwigs-universitat Freiburg

Albert-ludwigs-universitaet Freiburg

Toyota Motor Europe Nv/sa

Cogvis Software Und Consulting Gmbh

Mark Van Loock

Wolfram Burgard

Takashi Yamamoto

Yoshiaki Asahara

Sven Meier

Bastian Steder

Giorgio Grisetti

Michael Brandstoetter

Rainer Planinc

Christopher Pramerdorfer

Martin Kampel

Jugesh Sundram

Michael Krawez

Tim Caselitz

Jakob Knapp

Dimitri Accad

A method for simulating, at an instant, the illumination of an indoor scene observed by a camera and being illuminated by outdoor light, the method comprising: a first preliminary phase including: obtaining a reflectance map of the scene elaborating normalized radiosity maps for the contribution of the sky and the ground, a second phase carried out within a first given duration from the instant including: obtaining the position of the sun, obtaining a normalized radiosity map for the contribution of the sun, a third phase, including: acquiring an image of the scene, determining brightness scale parameters for the ground, the sky, and the sun. The disclosure also proposes tracking the camera position.

Method for simulating the illumination of an indoor scene observed by a camera illuminated by outdoor light and system

The disclosed subject matter relates to a method for determining a type and a state of an object of interest, comprising: generating a depth map of a scene by means of a depth sensor, the scene containing the object of interest and an occlusion object lying between the depth sensor and the object of interest; computing three 2D occupancy views, each in a different viewing direction, and three 2D occlusion views; feeding each of said occupancy and occlusion views into a different input of a trained convolutional neural network; receiving both a class and a bounding box of the object of interest from the convolutional neural network; and determining the type of the object of interest and the state of the object of interest. The disclosed subject matter further relates to a system for carrying out said method.

Method for determining a type and a state of an object of interest

To carry out satisfactory object recognition in a short time. An object recognition method in accordance with an exemplary aspect of the present invention is an object recognition method for recognizing a target object by using a preliminarily-created object model. The object recognition method generates a range image of an observed scene, detects interest points from the range image, extracts first features, the first features being features of an area containing the interest points, carries out a matching process between the first features and second features, the second features being features of an area in the range image of the object model, calculates a transformation matrix based on a result of the matching process, the transformation matrix being for projecting the second features on a coordinate system of the observed scene, and recognizes the target object with respect to the object model based on the transformation matrix.

Object recognition method, object recognition apparatus, and autonomous mobile robot

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Westmeerbeek, Belgium

Mark Van Loock