Improving Active Vision System Categorization Capability Through Histogram of Oriented Gradients

Olalekan Adebayo Lanihun, Bernard Tiddeman, Elio Tuci, Patricia Shaw

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

4 Dyfyniadau (Scopus)

Crynodeb

In the previous work of Mirolli et al. [1], an active vision system controlled by a genetic algorithm evolved neural network was used in simple letter categorization system, using gray-scale average noise filtering of an artificial eye retina. Lanihun et al. [2] further extends on this work by using Uniform Local Binary Patterns (ULBP) [4] as a pre-processing technique, in order to enhance the robustness of the system in categorizing objects in more complex images taken from the camera of a Humanoid (iCub) robot . In this paper we extend on the work in [2], using Histogram of Oriented Gradients (HOG) [5] to improve the performance of this system for the same iCub image problem. We demonstrate this ability by performing comparative experiments among the three methods. Preliminary results show that the proposed HOG method performed better than the ULBP and the gray-scale averaging [1] methods. The approach of better pre-processing with HOG gives a representation that could translate to improve motor responses in enhancing categorization capability for robotic vision control systems.
Iaith wreiddiolSaesneg
TeitlTowards Autonomous Robotic Systems - 16th Annual Conference, TAROS 2015, Proceedings
Is-deitl16th Annual Conference, TAROS 2015, Liverpool, UK, September 8-10, 2015, Proceedings
GolygyddionClare Dixon, Karl Tuyls
CyhoeddwrSpringer Nature
Tudalennau143-148
Nifer y tudalennau6
ISBN (Electronig)978-3-319-22416-9
ISBN (Argraffiad)978-3-319-22415-2
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 27 Gorff 2015

Cyfres gyhoeddiadau

EnwLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Cyfrol9287
ISSN (Argraffiad)0302-9743
ISSN (Electronig)1611-3349

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