Human detection and activity recognition is very important research area in the healthcare,
video surveillance, pedestrian detection, intelligent vehicle system and home care center …

Pedestrian detection is a key problem in computer vision and is currently addressed with
increasingly complex solutions involving compute-intensive features and classification …

Support Vector Machines (SVMs) are still one of the most popular and precise classifiers.
The Radial Basis Function (RBF) kernel has been used in SVMs to separate among classes …

This book is an introduction to social data analytics along with its challenges and
opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on …

Recent advances in search and rescue methods include the use of unmanned aerial
vehicles (UAVs), to carry out aerial monitoring of terrains to spot lost individuals. To date …

Image analysis is a key area in the computer vision domain that has many applications.
Genetic Programming (GP) has been successfully applied to this area extensively, with …

Locally normalized Histogram of Oriented Gradient (HOG) algorithm originally proposed by
Dalal & Triggs presents excellent results for pedestrian detection. However, as the demand …

Histogram of oriented gradient (HOG) features in combination with support vector machine
(SVM) classification are still widely reported as a de facto standard benchmark to evaluate …

Detecting faces in images is a key step in numerous computer vision applications, such as
face recognition or facial expression analysis. Automatic face detection is a difficult binary …

Applying convolution methods to domains that lack regular underlying structures is a
challenging task for 3D vision. Existing methods require the manual design of feature …