ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN ALGORITMA HORN-SCHUNCK DAN LUCAS-KANADE - Wahyu Supriyatin (Ilmu Komputer, FMIPA, Universitas Pakuan, 2020)
Computer vision same function as human eye, the ability to see or look objects passing by. Object tracking is one of computer vision. Object tracking aims is to recognize and identifying object pass and determine how many.This research was conducted by comparing the two algorithms in Optical Flow, the Horn-Schunck and the Lucas-Kanade algorithm. The test was carried out using two videos obtained from the Matlab library. The resolution of the video used in this study is same, 120x160. The camera used to pick up the objects in this study is placed in one position. The test is carried out using simulation parameters specified in each algorithm. Both algorithms successfully recognize and detect objects and can count how many objects are in a frame. In the same testing duration time simulation makes the Lucas-Kanade algorithm have a faster total record time than Horn-Schunck in recognizing and detecting of objects.