Vision based road lane tracking using macro block temporal predictions
The Vision Based Road Lane Tracking using Macro Block (MB) Temporal Predictions is a method aimed to further advance the active research of using machine vision in detecting and tracking road lane markings. These researches are always focusing on both accuracy and complexity of the systems output. T...
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oai:animorepository.dlsu.edu.ph:etd_masteral-112192021-01-18T07:41:31Z Vision based road lane tracking using macro block temporal predictions Roxas, Edison A. The Vision Based Road Lane Tracking using Macro Block (MB) Temporal Predictions is a method aimed to further advance the active research of using machine vision in detecting and tracking road lane markings. These researches are always focusing on both accuracy and complexity of the systems output. The survey conducted by McCall and Trivedi [4] summarizes a comprehensive study of existing methods, none of which uses Macro Blocking. The study focused on the characteristic of each MB subjected to different conditions of detecting, tracking and predicting of road lanes. Several experiments were done repeatedly to quantify the effectiveness of the study such as accuracy of MB, complexity of system, and MSE. 2013-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_masteral/4381 Master's Theses English Animo Repository |
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De La Salle University |
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De La Salle University Library |
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English |
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The Vision Based Road Lane Tracking using Macro Block (MB) Temporal Predictions is a method aimed to further advance the active research of using machine vision in detecting and tracking road lane markings. These researches are always focusing on both accuracy and complexity of the systems output. The survey conducted by McCall and Trivedi [4] summarizes a comprehensive study of existing methods, none of which uses Macro Blocking. The study focused on the characteristic of each MB subjected to different conditions of detecting, tracking and predicting of road lanes. Several experiments were done repeatedly to quantify the effectiveness of the study such as accuracy of MB, complexity of system, and MSE. |
| format |
text |
| author |
Roxas, Edison A. |
| spellingShingle |
Roxas, Edison A. Vision based road lane tracking using macro block temporal predictions |
| author_facet |
Roxas, Edison A. |
| author_sort |
Roxas, Edison A. |
| title |
Vision based road lane tracking using macro block temporal predictions |
| title_short |
Vision based road lane tracking using macro block temporal predictions |
| title_full |
Vision based road lane tracking using macro block temporal predictions |
| title_fullStr |
Vision based road lane tracking using macro block temporal predictions |
| title_full_unstemmed |
Vision based road lane tracking using macro block temporal predictions |
| title_sort |
vision based road lane tracking using macro block temporal predictions |
| publisher |
Animo Repository |
| publishDate |
2013 |
| url |
https://animorepository.dlsu.edu.ph/etd_masteral/4381 |
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