This paper deals with the algorithm for extracting human skin region through skin detection and skin segmentation from a video. At first, the change of shot is detected and then extraction of image (if any) is done from detected shots. Once the image is detected, it gets converted into an HSV image and then skin segmentation is done. Conversion of an image into an HSV helps to work in single variable (i.e. variable being the only hue value). This algorithm will automatically provide change of shots, skin detection, skin segmentation and then extraction of the face. This entire algorithm is done under the Image Processing Toolbox (IPT) of MATLAB. Moreover, Fuzzy Logic is also used in this paper for thresholding the hue values for skin segmentation and skin detection. This paper provides a detailed idea of extracting the human face from a video automatically.

Today's epoch christened as the modern epoch, is the epoch of information and technologies. No field is untouched with the emergence of technologies. In different segments of agriculture, numerous technologies have been employed extensively. Machine learning has extensively been employed in every field today. It is composed of high-performance computing and big data technologies. Machine learning (ML) and its variants have been employed in different domains of agriculture like yield prediction, weed detection, disease detection, water management, soil management, livestock production, etc. Machine learning techniques have emerged as a boon to agriculture and have increased the quality and quantity of agricultural products. In this chapter, some applications of machine learning technologies in agriculture have been explored.

Using time series data obtained from accelerometer and gyroscope sensors on an iPhone 6s, the authors address the topic of human activity and attribute detection. The collection contains time series data from 24 subjects who completed six activities in 15 trials. The aim is to appropriately identify the six activities using machine learning techniques. The usage of a convolutional neural network (CNN) for the categorization of human activity and attribute identification data obtained from accelerometer and gyroscope sensors on an iPhone 6s is proposed in this research. The collection contains time series data from 24 subjects who completed six activities in 15 trials. The study begins by pre-processing the data by transforming the folders into class labels and plotting the time series data. The time-series data is made up of multivariate data from both the accelerometer and gyroscope sensors, totaling 12 characteristics. The accelerometer sums up two acceleration vectors, gravity, and user acceleration, which may be distinguished using core motion tracking technology.

Over the last few decades, remarkable infrastructure growths have been noticed in security-related issues throughout the world. So, with increased demand for Security, Video-based Surveillance has become an important area for the research. An Intelligent Video Surveillance system basically censored the performance, happenings, or changing information usually in terms of human beings, vehicles or any other objects from a distance by means of some electronic equipment (usually digital camera). The scopes like prevention, detection, and intervention which have led to the development of real and consistent video surveillance systems are capable of intelligent video processing competencies. In broad terms, advanced video-based surveillance could be described as an intelligent video processing technique designed to assist security personnel’s by providing reliable real-time alerts and to support efficient video analysis for forensic investigations. This chapter deals with the various requirements for designing a robust and reliable video surveillance system. Also, it is discussed the different types of cameras required in different environmental conditions such as indoor and outdoor surveillance. Different modeling schemes are required for designing of efficient surveillance system under various illumination conditions.