Object detection and recognition are an integral part of computer vision systems. In computer vision, the work begins with a breakdown of the scene into components that a computer can see and analyse.

Recently, neural network models of visual object recognition ... We computed the ROC graphs for humans and the HMAX model for each of the 12 classes and used the EER for the comparison. ...

Graph matching remains a core challenge in computer vision, where establishing correspondences between features is crucial for tasks such as object recognition, 3D reconstruction and scene ...

Automated object recognition -- and more generally scene analysis -- from photographs and videos is the grand challenge of computer vision. This course presents the image, object, and scene models, as ...

The topic of model-building for 3-D objects is examined. Most 3-D object recognition systems construct models either manually or by training. Neither approach has been very satisfactory, particularly ...

This article describes the simple step by step system, to teach object recognition and tracking in computer vision systems. Methodology is based on object recognition system complexity incrementation.

The talk will cover visual recognition from the early 90’s, including handwritten digit and face detection, to the current state-of-the-art in deep learning applied to object categorization.

While traditional approaches in pattern recognition and computer vision have continued to evolve, along with the advances of artificial intelligence (AI), this unique compendium presents recent ...