CUED Publications database

Initializing Vision Based Trackers Using Semantic Texton Forests

Park, MW and Jog, GM and Brilakis, I (2011) Initializing Vision Based Trackers Using Semantic Texton Forests. In: 28th International Symposium on Automation and Robotics in Construction (ISARC 2011), 2011-6-29 to 2011-7-2, Seoul, Korea pp. 379-384..

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Vision based tracking can provide the spatial location of project related entities such as equipment, workers, and materials in a large-scale congested construction site. It tracks entities in a video stream by inferring their motion. To initiate the process, it is required to determine the pixel areas of the entities to be tracked in the following consecutive video frames. For the purpose of fully automating the process, this paper presents an automated way of initializing trackers using Semantic Texton Forests (STFs) method. STFs method performs simultaneously the segmentation of the image and the classification of the segments based on the low-level semantic information and the context information. In this paper, STFs method is tested in the case of wheel loaders recognition. In the experiments, wheel loaders are further divided into several parts such as wheels and body parts to help learn the context information. The results show 79% accuracy of recognizing the pixel areas of the wheel loader. These results signify that STFs method has the potential to automate the initialization process of vision based tracking.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Artificial intelligence Automatic identification Image processing Tracking Information technology
Divisions: Div D > Construction Engineering
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 20:31
Last Modified: 17 Jul 2018 06:35