In many recent object recognition systems, feature extraction
stages are generally composed of a filter bank, a
non-linear transformation, and some sort of feature pooling
layer...
Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio R...
Abstract. Many applications of 3D object recognition, such as augmented reality or robotic manipulation, require an accurate solution for the 3D pose of the recognized objects. Thi...
—We study the problem of actively searching for an object in a 3D environment under the constraint of a maximum search time, using a visually guided humanoid robot with twentysix...
Alexander Andreopoulos, Stephan Hasler, Heiko Wers...
Many different constructions for (t, m, s)-nets and (t, s)-sequences are known today. Propagation rules as well as connections to other mathematical objects make it difficult to ...
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...