An Automatic Image Content Retrieval Method for better Mobile Device Display User Experiences

by   Alessandro Bruno, et al.

A growing number of commercially available mobile phones come with integrated high-resolution digital cameras. That enables a new class of dedicated applications to image analysis such as mobile visual search, image cropping, object detection, content-based image retrieval, image classification. In this paper, a new mobile application for image content retrieval and classification for mobile device display is proposed to enrich the visual experience of users. The mobile application can extract a certain number of images based on the content of an image with visual saliency methods aiming at detecting the most critical regions in a given image from a perceptual viewpoint. First, the most critical areas from a perceptual perspective are extracted using the local maxima of a 2D saliency function. Next, a salient region is cropped using the bounding box centred on the local maxima of the thresholded Saliency Map of the image. Then, each image crop feds into an Image Classification system based on SVM and SIFT descriptors to detect the class of object present in the image. ImageNet repository was used as the reference for semantic category classification. Android platform was used to implement the mobile application on a client-server architecture. A mobile client sends the photo taken by the camera to the server, which processes the image and returns the results (image contents such as image crops and related target classes) to the mobile client. The application was run on thousands of pictures and showed encouraging results towards a better user visual experience with mobile displays.


page 2

page 4


Mobile Multi-View Object Image Search

High user interaction capability of mobile devices can help improve the ...

Can Image Retrieval help Visual Saliency Detection?

We propose a novel image retrieval framework for visual saliency detecti...

An Analysis of Object Embeddings for Image Retrieval

We present an analysis of embeddings extracted from different pre-traine...

Color and Shape Content Based Image Classification using RBF Network and PSO Technique: A Survey

The improvement of the accuracy of image query retrieval used image clas...

Understanding Visual Saliency in Mobile User Interfaces

For graphical user interface (UI) design, it is important to understand ...

Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data

Good results on image classification and retrieval using support vector ...

Text Extraction and Retrieval from Smartphone Screenshots: Building a Repository for Life in Media

Daily engagement in life experiences is increasingly interwoven with mob...

Please sign up or login with your details

Forgot password? Click here to reset