Authors:
Ashish Khare
1
;
Hiranmay Ghosh
1
and
Jaideep Shankar Jagannathan
2
Affiliations:
1
TCS Innovation Labs, Tata Consultancy Services Ltd, India
;
2
Freescale SemiconductorIndia Ltd, India
Keyword(s):
Online shopping, Query-by-Example, Content-based Image Retrieval, SIFT, PCA-SIFT, Image Features Indexing, R-Tree.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Feature Extraction
;
Features Extraction
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Implementation of Image and Video Processing Systems
;
Informatics in Control, Automation and Robotics
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
;
Statistical Approach
Abstract:
In this paper, we present a new example based approach to search for a particular product based on its visual properties. A user can take a photo of a product package with a cell-phone or webcam and submit it to an online shopping portal for finding the product details. We search a product image database for the distinctive visual features on the query image to locate the desired product. We use PCA-SIFT feature for robust retrieval, to account for possible imperfections in the query image due to uncontrolled user environment. We use Oracle Java R-Tree to index image features to realize a scalable system. We establish robustness and scalability of our approach by conducting several experiments on fairly large prototype implementations.