3D Object Detection with Stereo Vision and Transformer

Samin, Abid Ahsan; Hassan, Abdullah; Khan, Md. Rakib Hossain

dc.contributor.author	Samin, Abid Ahsan
dc.contributor.author	Hassan, Abdullah
dc.contributor.author	Khan, Md. Rakib Hossain
dc.date.accessioned	2023-04-28T03:38:40Z
dc.date.available	2023-04-28T03:38:40Z
dc.date.issued	2022-05-30
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dc.identifier.uri	http://hdl.handle.net/123456789/1857
dc.description	Supervised by Dr. Md. Kamrul Hasan, Professor, Department of Computer Science and Engineering(CSE), Islamic University of Technology (IUT) Board Bazar, Gazipur-1704, Bangladesh. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022	en_US
dc.description.abstract	Identifying 3D objects with computer vision in a precise manner has been a challenging task in the field of autonomous driving. Partly because it requires proper depth estimation. Until now, Li-DAR technology has been used to achieve this task which is precise but also expensive. The introduction of pseudo Li-DAR promises an alternative approach which is cheaper with fairly good precision. However, pseudo Li-DAR can be replaced with 2D image representation with similar precision. Transformer is another technology which is widely used to process sequential data. Recent studies show that transformer can also be used for object detection purposes. In this literature, we look into the concept of pseudo Li-DAR, image representation of depth and detection transformer(DETR). Later, we introduce a new approach of using image based depth output with DETR to achieve accurate object detection. Finally, we compare our results with other available methods used for object detection in order to establish a benchmark.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur, Bangladesh	en_US
dc.subject	3D Object Detection, KITTI, Autonomous Driving	en_US
dc.title	3D Object Detection with Stereo Vision and Transformer	en_US
dc.type	Thesis	en_US