Automatic Synchronization of Multi-User Photo Galleries

In this paper we address the issue of photo galleries synchronization, where pictures related to the same event are collected by different users. Existing solutions to address the problem are usually based on unrealistic assumptions, like time consistency across photo galleries, and often heavily rely on heuristics, limiting therefore the applicability to real-world scenarios. We propose a solution that achieves better generalization performance for the synchronization task compared to the available literature. The method is characterized by three stages: at first, deep convolutional neural network features are used to assess the visual similarity among the photos; then, pairs of similar photos are detected across different galleries and used to construct a graph; eventually, a probabilistic graphical model is used to estimate the temporal offset of each pair of galleries, by traversing the minimum spanning tree extracted from this graph. The experimental evaluation is conducted on four publicly available datasets covering different types of events, demonstrating the strength of our proposed method. A thorough discussion of the obtained results is provided for a critical assessment of the quality in synchronization.Comment: ACCEPTED to IEEE Transactions on Multimedi

Personal Photo Indexing

Sorting one’s own private photo collection is a time consuming and tedious task. We demonstrate our event-centered approach to perform this task fully automatically. In the course of the demonstration, we either use our own photo collections, or invite the conference visitors to bring their own cameras and photos. We will sort the photos into a semantically meaningful hierarchy for the users within a couple of minutes. Events as a media aggregator allow a user to manage and annotate a photo collection in more convenient and natural to the human being way. Based on the recognized user behavior the application is able to re- veal the nature of an event and build its hierarchy with a event/sub-event relationship. One important prerequisite of our approach is a precise GPS based spatial annotation of the photos. To accommodate for devices without GPS chips or temporary low GPS perception, we propose an approach to enrich the collection with automatically estimated GPS data by semantically interpolating possible routes of the user. We are positive that we can provide a well received service for the conference visitors, especially since the conference venue will trigger a lot of memorable photos. Large scale experimental validation showed that the approach is able to recreate a user’s desired hierarchy with an F-measure of about 0.8

Smartphone picture organization: a hierarchical approach

We live in a society where the large majority of the population has a camera-equipped smartphone. In addition, hard drives and cloud storage are getting cheaper and cheaper, leading to a tremendous growth in stored personal photos. Unlike photo collections captured by a digital camera, which typically are pre-processed by the user who organizes them into event-related folders, smartphone pictures are automatically stored in the cloud. As a consequence, photo collections captured by a smartphone are highly unstructured and because smartphones are ubiquitous, they present a larger variability compared to pictures captured by a digital camera. To solve the need of organizing large smartphone photo collections automatically, we propose here a new methodology for hierarchical photo organization into topics and topic-related categories. Our approach successfully estimates latent topics in the pictures by applying probabilistic Latent Semantic Analysis, and automatically assigns a name to each topic by relying on a lexical database. Topic-related categories are then estimated by using a set of topic-specific Convolutional Neuronal Networks. To validate our approach, we ensemble and make public a large dataset of more than 8,000 smartphone pictures from 40 persons. Experimental results demonstrate major user satisfaction with respect to state of the art solutions in terms of organization.Peer ReviewedPreprin

Image metadata estimation using independent component analysis and regression

In this paper, we describe an approach to camera metadata estimation using regression based on Independent Component Analysis (ICA). Semantic scene classification of images using camera metadata related to capture conditions has had some success in the past. However, different makes and models of camera capture different types of metadata and this severely hampers the application of this kind of approach in real systems that consist of photos captured by many different users. We propose to address this issue by using regression to predict the missing metadata from observed data, thereby providing more complete (and hence more useful) metadata for the entire image corpus. The proposed approach uses an ICA based approach to regression

The Relevance of Information Sources on Adoption of Precision Farming Technologies by Cotton Producers

Replaced with revised version of paper 02/16/11.strategic communication, competitiveness, extension, economics of information, technology diffusion, technology supply, communication methods, knowledge management, Production Economics, Research and Development/Tech Change/Emerging Technologies, Teaching/Communication/Extension/Profession, D22, D80, D82, D83, Q12, Q16,