TY  - THES
U1  - Bachelor Thesis
A1  - Satharasi, Rudresh Naidu
T1  - Detection and Classification of Video sequence during Night-Time
N2  - Object detection and classification is active field of research inmachine learning and computervision. Depending on the application there are different limitations to adjust to, but also possibilities to take advantage of. In my thesis, We focus on classification and detection of video sequence during night-time and the proposed method is robust since it does use image thresholding [8] which is commonly use in other methods and the thesis uses histograms of oriented gradients (HOG) [37] as features and support vector machine (SVM) [74] as classifier. It is of great importance that the extracted features from the images should be robust and distinct enough to help the classifier distinguish between high-beam and a low-beam. The classifier is part of the object detection which predicts whether or not a testing image matches one group or the other. In our case that is predicting whether or not an image belongs to high or low-beam sequence.
KW  - Objekterkennung
Y2  - 2018
ER  -