Sri Vidya M S

Traditionally wired keyboard and mouse were used as inputting devices to the computer system. These models had many drawbacks like hardware bulkiness and inefficiency due to delay. In this paper the new proposed system will input data using hand recognition and motion analysis. Webcam is used as the primary device to capture the hand gesture. These images are preprocessed to remove noise and for bit reduction. After the image preprocessing feature extraction and segmentation are done. CNN algorithms are used for object detection by identifying the features of the hand. For the system to identify the gesture, a number of images are used for training the system. This process is known as Features training. Once the features and the gestures are recognized, it is mapped to a particular function of the mouse and keyboard. � 2019 IEEE.

Physical abuse has become a societal problem. Mostly children, women and old age people are vulnerable to it especially in cases of domestic violence or workplace aggression. Reporting it is in itself a challenge especially if there is a pre-existing relationship between the abuser and victim. In this paper we propose a deep learning technique for human action recognition and human pose identification to tackle physical abuse by detecting it in real time. 3D convolution neural network (CNN) architecture is built using 3D convolution feature extractors which extract both temporal and spatial data in the video. With multiple convolution layer and subsampling layer, the input video has been converted into feature vector. Human pose estimation is done using the detection of key points on the body. Using these points and tracking them from one frame to another gives spatial-temporal features to feed into neural network (NN). We present metrics to measure the accuracies of such systems where real time reporting and fault tolerance capabilities are of utmost importance. Weighted metrics shows accuracy of about 89.42% with precision of about 85.82% and thus shows the effectiveness of the system. � 2021, Institute of Advanced Engineering and Science. All rights reserved.