A comparative study on mobile visual recognition

Authors:
Elisavet Chatzilari;Georgios Liaros;Spiros Nikolopoulos;Yiannis Kompatsiaris
Affiliations:
Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece,Centre for Vision, Speech and Signal Processing University of Surrey Guildford, UK;Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece,Dept. of Informatics, Ionian University, Kerkyra, Greece;Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece;Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
Venue:
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
Year:
2013

Citing 17
Cited 0

Support-Vector Networks

Machine Learning
Object Recognition from Local Scale-Invariant Features

ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
A Performance Evaluation of Local Descriptors

IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Speeded-Up Robust Features (SURF)

Computer Vision and Image Understanding
Real-Time Computerized Annotation of Pictures

IEEE Transactions on Pattern Analysis and Machine Intelligence
LIBLINEAR: A Library for Large Linear Classification

The Journal of Machine Learning Research
Outdoors augmented reality on mobile phone using loxel-based visual feature organization

MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Pose tracking from natural features on mobile phones

ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Visual Word Ambiguity

IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluating Color Descriptors for Object and Scene Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
BRIEF: binary robust independent elementary features

ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Image classification using super-vector coding of local image descriptors

ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Machine learning for high-speed corner detection

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
FREAK: Fast Retina Keypoint

CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
ORB: An efficient alternative to SIFT or SURF

ICCV '11 Proceedings of the 2011 International Conference on Computer Vision

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work we perform an extensive comparative study of approaches for mobile visual recognition by simultaneously evaluating the performance and the computational cost of state-of-the-art key-point detection, feature extraction and encoding algorithms. Every step is independently tested so that its contribution to the final computational cost can be measured. The widely used OpenCV library is utilized for the implementation of the algorithms, while the evaluation is performed on the PASCAL VOC 2007 dataset, a challenging real world dataset crawled from the web. Our study identifies the algorithmic configurations that manage to optimally balance performance and computational cost, and provide a viable solution for real time mobile visual recognition.