Object detection and tracking are two fundamental tasks in multicamera surveillance. This
paper proposes a framework for achieving these tasks in a nonoverlap** multiple camera …

Using geometric landmarks like lines and planes can increase navigation accuracy and
decrease map storage requirements compared to commonly-used LiDAR point cloud maps …

Real-world multi-view data may manifest as point-clouds, but their meaningful structure often
resides on a lower dimensional manifold embedded in the higher dimensional space …

Using pole and plane objects in lidar SLAM can increase accuracy and decrease map
storage requirements compared to commonly-used point cloud maps. However, place …

In the private cloud data center, security participated a fundamental position amid the
storage of a voluminous amount of information that is intended to share among various …

Incorporating metric learning in visual tracking applications has been demonstrated to be
able to improve tracking performance. However, the optimal metric is mainly derived based …

We present a novel method for robust tracking in video frame sequences via L1-Grassmann
manifolds. The proposed method represents adaptively the target as a point on the …

Deep neural networks have been widely applied to visual tracking and obtained significant
improvements in tracking accuracy and robustness. But some algorithms of this kind suffer …

Recent attempts demonstrate that learning an appropriate distance metric in visual tracking
applications can improve the tracking performance. However, the existing metric learning …

The success of sparse representation, in face recognition and visual tracking, has attracted
much attention in computer vision in spite of its computational complexity. These sparse …