2D images are not sufficient for testing 3D object recognition
نویسندگان
چکیده
منابع مشابه
Learning 3D Object Recognition Models from 2D Images
To recognize an object in an image one must have some internal model of how that object may appear. We show how to learn such a model from a series of training images depicting a class of objects. The model represents a 3D object by a set of characteristic views, each defining a probability distribution over variation in object appearance. Features identified in an image through perceptual orga...
متن کامل2D observers for human 3D object recognition?
In human object recognition, converging evidence has shown that subjects' performance depends on their familiarity with an object's appearance. The extent of such dependence is a function of the inter-object similarity. The more similar the objects are, the stronger this dependence will be and the more dominant the two-dimensional (2D) image-based information will be. However, the degree to whi...
متن کاملAre Edges Sufficient for Object Recognition ?
The authors argue that the concept of "edges" as used in current research on object recognition obscures the significant difficulties involved in interpreting stimulus information. Edges have sometimes been operationalized as line drawings, which can be an invalid and misleading practice. A new method for evaluating the utility of edge information, operationalized as the outputs of a local, sig...
متن کامل2D Observers in 3D Object Recognition
Converging evidence has shown that human object recognition depends on the observers' familiarity with objects' appearance. The more similar the objects are, the stronger this dependence is, and the more important two-dimensional (2D) image information is to discriminate these objects from one another. The degree to which 3D structural information is used, however, still remains an area of stro...
متن کاملNeural network based 2D/3D fusion for robotic object recognition
We present a neural network based fusion approach for realtime robotic object recognition which integrates 2D and 3D descriptors in a flexible way. The presented recognition architecture is coupled to a real-time segmentation step based on 3D data, since a focus of our investigations is real-world operation on a mobile robot. As recognition must operate on imperfect segmentation results, we con...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Vision
سال: 2010
ISSN: 1534-7362
DOI: 10.1167/8.6.514