Vision-assisted object tracking

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2012

Öğrenci: KEMAL ARDA ÖZERTEM

Danışman: ABDULLAH AYDIN ALATAN

Özet:

In this thesis, a video tracking method is proposed that is based on both computer vision and estimation theory. For this purpose, the overall study is partitioned into four related subproblems. The first part is moving object detection; for moving object detection, two different background modeling methods are developed. The second part is feature extraction and estimation of optical flow between video frames. As the feature extraction method, a well-known corner detector algorithm is employed and this extraction is applied only at the moving regions in the scene. For the feature points, the optical flow vectors are calculated by using an improved version of Kanade Lucas Tracker. The resulting optical flow field between consecutive frames is used directly in proposed tracking method. In the third part, a particle filter structure is build to provide tracking process. However, the particle filter is improved by adding optical flow data to the state equation as a correction term. In the last part of the study, the performance of the proposed approach is compared against standard implementations particle filter based trackers. Based on the simulation results in this study, it could be argued that insertion of vision-based optical flow estimation to tracking formulation improves the overall performance.