Multifeatures Based Compressive Sensing Tracking

Compressive Sensing in Visual Tracking

Visual tracking is an important component of many video surveillance systems. Specifically, visual tracking refers to the inference of physical object properties (e.g., spatial position or velocity) from video data. This is a well-established problem that has received a great deal of attention from the research community (see, e.g., the survey (Yilmaz et al., 2006)). Classical techniques often ...

Compressive sensing

Michael B. Wakin is the Ben L. Fryrear Associate Professor in the Department of Electrical Engineering and Computer Science at the Colorado School of Mines (CSM). Dr. Wakin received a B.S. in electrical engineering and a B.A. in mathematics in 2000 (summa cum laude), an M.S. in electrical engineering in 2002, and a Ph.D. in electrical engineering in 2007, all from Rice University. He was an NSF...

LCSiLEACH: LWZ Compressive Sensing Based iLEACH

In the application based WSNs circumstance, vitality and transmission capacity of the sensors are esteemed assets and vital to consume competently. Data collection at the sink by individual sensor nodes results in flooding of the requests which results in most extreme energy use. To decrease this issue another data aggregation technique has been used in this paper which has enhanced the executi...

Compressive Sensing

Compressive sensing is a new type of sampling theory, which predicts that sparse signals and images can be reconstructed from what was previously believed to be incomplete information. As a main feature, efficient algorithms such as l1-minimization can be used for recovery. The theory has many potential applications in signal processing and imaging. This chapter gives an introduction and overvi...

Compressive Sensing