Incremental and hierarchical classification of a personal image collection on mobile devices

نویسنده

  • Antoine Pigeau
چکیده

Browsing multimedia collection on mobile devices raises the needs for new multimedia indexing solutions. In this paper, we focus on the management of personal image collections. We propose a method to simplify the browsing task on such a collection. The contributions reside in an incremental hierarchical algorithm, a method to provide a textual representation of the groups obtained and an algorithm to build a geo-temporal view of the collection. The proposed incremental hierarchical algorithm builds a temporal tree from the time stamp of each image. We opt here for a combination of a supervised clustering and an incremental algorithm based on mixture model. Good properties of the hierarchy are determined automatically thanks to the Integrated Likelihood Criterion (ICL). Based on the events obtained, a textual representation is proposed and then used to improve our temporal classification, combining geographical and temporal information. Results are validated on several real user collections with our prototype MyOwnLife.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Robust Method for E-Maximization and Hierarchical Clustering of Image Classification

We developed a new semi-supervised EM-like algorithm that is given the set of objects present in eachtraining image, but does not know which regions correspond to which objects. We have tested thealgorithm on a dataset of 860 hand-labeled color images using only color and texture features, and theresults show that our EM variant is able to break the symmetry in the initial solution. We compared...

متن کامل

Plant Classification in Images of Natural Scenes Using Segmentations Fusion

This paper presents a novel approach to automatic classifying and identifying of tree leaves using image segmentation fusion. With the development of mobile devices and remote access, automatic plant identification in images taken in natural scenes has received much attention. Image segmentation plays a key role in most plant identification methods, especially in complex background images. Wher...

متن کامل

A Hierarchical Classification Method for Breast Tumor Detection

Introduction Breast cancer is the second cause of mortality among women. Early detection of it can enhance the chance of survival. Screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. Computer-aided diagnosis can help physicians make a more accurate diagnosis. Materials and Methods Regarding the importance of separating normal and abnorm...

متن کامل

Spectral-spatial classification of hyperspectral images by combining hierarchical and marker-based Minimum Spanning Forest algorithms

Many researches have demonstrated that the spatial information can play an important role in the classification of hyperspectral imagery. This study proposes a modified spectral–spatial classification approach for improving the spectral–spatial classification of hyperspectral images. In the proposed method ten spatial/texture features, using mean, standard deviation, contrast, homogeneity, corr...

متن کامل

Compression and network effect on content-based image retrieval on Java enabled mobile devices

In this paper we present compression and network effect on content-based image retrieval on Java enabled mobile devices. We use client-server framework where client run on Java enabled mobile devices and servers on personal computer. Servers are designed to provide faster query results and compressed image items to the clients on request. Framework is tested on different networks by using diffe...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017