Case-Based Object Recognition

Model-based object recognition is a well-known task in Computer Vision. Usually, one object that can be generalized by a model should be detected in an image based on this model. Biomedical applications have the special quality that one object can have a great variation in appearance. Therefore the appearance of this object cannot be generalized by one model. A set of cases of the appearance of this object (sometimes 50 cases or more) is necessary to detect this object in an image. The recognition method is rather case-based object recognition than model-based object recognition. Case-based object recognition is a challenging task. It puts special requirements to the similarity measure and needs a matching algorithm that can work fast on a large number of cases. It also needs a case acquisition procedure that can capture the great variation in appearance of an object and generalize these data into a case description. In this paper we describe the chosen case representation, the similar...

• Type: Conference
• Year: 2004
• Where: EWCBR
• Authors: Petra Perner, Angela Bühring
• Keywords: Artificial Intelligence, Case-based Object Recognition, EWCBR 2004, Model-based Object Recognition, Object Recognition