INTERACTIVE MIRROR RECOGINITION SYSTEM IN SHOPPING MALLS BASED PATTERN RECOGINITION AND BACK PROPAGATION

ROOPSINGH TAKUR

Abstract


In this paper, we present a theoretical framing of the functions of a mirror by breaking of a mirror by breaking the synchrony between the state of a reference object and its reflection. This framing has problems when it displays an image on mirror. These problems are technical problems and illustrate the technical challenges in two different forms of electronic mirror systems for apparel shopping. The first example, the responsive mirror, is an intelligent video capture and access system for clothes shopping in physical stores that provides personalized asynchronous reflections of clothing items through an implicitly controlled human-computer interface. The responsive mirror employs computer vision and neural network techniques such as Back propagation algorithm to correct the errors and show the interpret the visual cues of the customer’s behavior from cameras to then display two different reflections of the customer on digital displays:1) the customer in previously worn clothing with matching pose and orientation. So there is a problem of error occurring in matching of samples inside the database. To optimize or solve the error we are using back propagation algorithm. 2) For searching the sample pattern of clothes in the database. We are using hash function to increase the search speed of identification dimensions and match the clothes according to that dimensions. In countertop responsive mirror that differs from the first in images do not respond to the real time movement of the customer but to frames in a recorded video so that motion of the customer in the different recordings are matched and searched in the database non sequentially. These instantiations of the mirror systems in fitting room and jewelry shopping scenarios are described, focusing on the system architecture and the intelligent computer vision components. The paper contributes a conceptualization of reflection, error correcting and searching the samples in the database through back propagation algorithm and hash function algorithm.

Key Words: Intelligent user interface, responsive mirror, pattern recognition, computer vision, back propagation, hash function.


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ISSN : 2251-1563