Titlebook: Computer Vision -- ECCV 2014; 13th European Confer David Fleet,Tomas Pajdla,Tinne Tuytelaars Conference proceedings 2014 Springer Internati

Nonconformist

https://doi.org/10.1007/978-3-319-55938-4 the annotated training data. In this paper, we formulate interest point detection as a supervised binary classification problem using a random forest as our classifier. We validate the accuracy of our method and compare our results to those of five state of the art methods on a new, standard benchmark.

BAN

Probability and Its Applications assumed to be unknown. A new synchronization algorithm for static or jointly moving cameras that see (possibly) different parts of a common rigidly moving object is also proposed. Proof-of-concept experiments that illustrate the performance of these methods are presented, as well as a comparison with a state-of-the-art approach.

Lyme-disease

Probability and Its Applicationsomponents over a large depth of field while still using a relatively small number of images (typically 25-30). We demonstrate the effectiveness of our approach by recovering high quality depth maps of scenes containing objects made of optically challenging materials such as wax, marble, soap, colored glass and translucent plastic.

Systemic

弄皱

dilute

3D Interest Point Detection via Discriminative Learning the annotated training data. In this paper, we formulate interest point detection as a supervised binary classification problem using a random forest as our classifier. We validate the accuracy of our method and compare our results to those of five state of the art methods on a new, standard benchmark.

点燃

Nucleate

Multi Focus Structured Light for Recovering Scene Shape and Global Illuminationomponents over a large depth of field while still using a relatively small number of images (typically 25-30). We demonstrate the effectiveness of our approach by recovering high quality depth maps of scenes containing objects made of optically challenging materials such as wax, marble, soap, colored glass and translucent plastic.

唤醒

Coplanar Common Points in Non-centric Cameras non-centric camera such as non-centric catadioptric mirrors. Finally, we present robust algorithms for extracting the CCPs from a single image and validate our theories and algorithms through experiments.

amorphous

Simultaneous Feature and Dictionary Learning for Image Set Based Face Recognition simultaneously from raw face images so that discriminative information can be jointly exploited. Extensive experimental results on four widely used face datasets show that our method achieves better performance than state-of-the-art image set based face recognition methods.