24/7 place recognition by view synthesis

The palmprint recognition scheme presented in this study combines a novel spiral feature extraction with a sparse representation of binarized statistical image

As for the comparison in a global context, the learning database is now composed for all the 100 objects of the 72 views without alteration and the recognition rate is computed

In this paper, we have proposed a parallel CUDA GPU based implementation of Sequence SLAM (SeqSLAM) for visual place recognition. SeqSLAM is a well-known successful approach for

’variation ratio gain’, which is aimed to prove theoretically the significance of color effect on low-resolution faces within well- known subspace face recognition frameworks.

(bottom) instead of using their proper selection schemes for filtering the correct matches, all methods use the geometric information of the matched supports to impose a

Note how the proposed method (f), based on densely sampled descriptors coupled with virtual view synthesis, obtains significantly higher inlier ratio (0.76) on this challenging

• Spatio-temporal SURF (ST-SURF): After video temporal segmentation and human action detection, we propose a new algorithm based on the extension of the SURF descriptors to the

We have designed a new convolutional neural network architecture that is trained for place recognition in an end-to-end manner from weakly supervised Street View Time Machine data..