http://20.198.91.3:8080/jspui/handle/123456789/8085 2026-03-09T08:44:01Z http://20.198.91.3:8080/jspui/handle/123456789/8615 Title: Vtrack: a novel visual object tracking benchmark database Authors: Mondal, Supriya Abstract: Visual object tracking is one of the most emerging areas in the field of computer vision. In recent years, significant progress has been achieved in this research area. Recent research in this field is mainly focused on data acquisition for creating new benchmark databases suitable for evaluating the performance of various tracking applications, designing several tracking methods, etc. The detection ability of any tracking method depends largely on the database on which it is trained. In order to perform efficient training of tracking methods and to properly evaluate their tracking capability, suitable benchmark databases containing videos or image frames with various attributes—e.g., occlusions, blurriness, etc, are required. The work conducted in this thesis is mainly focused on performing effective benchmarking of tracking capabilities of multiple methods. The main contribution of this thesis lies in designing a novel database, namely VTrack: a visual object tracking benchmark database comprising 25 videos containing thousands of frames with various attributes. 2022-01-01T00:00:00Z http://20.198.91.3:8080/jspui/handle/123456789/8610 Title: Time-frequency and fractal based analysis of EEG and sEMG signals under varying load conditions Authors: Bardhan, Anish Kumar 2022-01-01T00:00:00Z http://20.198.91.3:8080/jspui/handle/123456789/8607 Title: Classifying emotional features based on humour stimulus in three different states using eeg and machine learning Authors: Sen, Nahali 2022-01-01T00:00:00Z http://20.198.91.3:8080/jspui/handle/123456789/8569 Title: Brain signal analysis for classification of touch- induced affective emotion Authors: Bose, Dipdisha Abstract: This thesis paper introduces a novel approach to categorize the hemodynamic response of subjects due to arousal of touch induced affection classes such as Respect, Love, Fondness and Devotion using a TSK-based Type-2 Fuzzy classifier. The main contribution of the paper is to design the novel TSK-based Interval Type-2 Fuzzy classifier to classify the finer changes in affective emotions using the hemodynamic response of a subject, when she comes in contact with her mother, spouse, child and also conveys her prayer to a model/sculpture of God by holding it with her palms. Experiments undertaken reveal that the brain activation patterns vary in different sub-regions over distinct time-windows for individual emotions. Relative performance analysis and statistical validation confirm the superiority of the proposed TSK-based Interval Type-2 Fuzzy classifier. Moreover, the proposed scheme has successfully been applied for assessing subjective sensitivity of healthy as well as psychiatric disordered people. 2022-01-01T00:00:00Z