Differently from traditional two-dimensional texture images, the depth images of three-dimensional (3D) video systems have significant sparse characteristics under the certain transform basis, which make it possible for compressive sensing to represent depth information efficiently. Therefore, in this paper, a novel depth image coding scheme is proposed based on a block compressive sensing meth...

Compressed sensing is an advanced technique used in visual tracking problem. However, current research uses too many pre-knowledge, and cannot deal with quick object sensitively. Based on the problems, the paper proposes a new real-time visual tracking algorithm based on compressive sensing. On one hand, the algorithm uses the characteristics of compressive sensing, and make sure of the time co...

Data collection is performed by using the combination of compressive sensing and score based load balancing algorithm. To make the energy efficient network, the score based load balancing algorithm finds the path for routing the data towards the destination. The sensor nodes are divided into clusters and each cluster has one cluster head depending on their energy. The compressive sensing compre...

This paper proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs Swarm Intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate respectively. The main contribution of this paper is to extend Swarm Intelligence algorithms to build a routing tree in such a way that ...

In this paper we propose a new framework for capturing light transport data of a real scene, based on the recently developed theory of compressive sensing. Compressive sensing offers a solid mathematical framework to infer a sparse signal from a limited number of non-adaptive measurements. Besides introducing compressive sensing for fast acquisition of light transport to computer graphics, we d...

The accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time...

Compressive sensing is a new technique utilized for energy efficient data gathering in wireless sensor networks. It is characterized by its simple encoding and complex decoding. The strength of compressive sensing is its ability to reconstruct sparse or compressible signals from small number of measurements without requiring any a priori knowledge about the signal structure. Considering the fac...