Prihatmanto A S
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The Implementation of Object Recognition using Deformable Part Model (DPM) with Latent SVM on Lumen Robot Friend Kurniawan A; Saputra R; Marzuki Marzuki; Febrianti M S; Prihatmanto A S
International Conference on Engineering and Technology Development (ICETD) 2017: 4rd ICETD 2017
Publisher : Bandar Lampung University (UBL)

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Abstract

Object recognition is part of image processing. It is used to recognize the surrounding objects based on their features, then they are processed further to obtain valid data information that can be used for other purposes. Currently, object recognition is mostly used by robot developers as one of the features in humanoid robot. One of the recent challenges occurring in humanoid robot is how the robot detects and localizes generic objects from categories such as human or car in static images using sensory visuals. It is a difficult problem since objects in such categories vary both in appearance and shape. For example, it is difficult to recognize an object that most of its shape is blocked by other objects. To solve the problem, researcher used Deformable Part Model and latent svm methods, where the data collection was performed through Library Research and Field Research approaches. The conclusion of this research is that recognition to objects using deformable part model provides a passable accuracy. After 3 experiments had been performed, system was able to recognize objects with highest reach by 88%.