Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
We describe an approach to understanding evolved programs for a real world object detection problem, that of finding orthodontic landmarks in cranio-facial X-Rays. The approach in...
Victor Ciesielski, Andrew Innes, Sabu John, John M...
In this paper we address two closely related problems. The first is the object detection problem, i.e., the automatic decision of whether a given image represents a known object o...
We propose a method for object detection in cluttered real images, given a single hand-drawn example as model. The image edges are partitioned into contour segments and organized i...
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo...
Reliable detection of fiducial targets in real-world images is addressed in this paper. We show that even the best existing schemes are fragile when exposed to other than laborator...