Digital Photo Management

Organizing personal photo collections

FXPAL’s Photo Application, also known as the Rich Media Organizer (RMO), is a tool for managing personal photo collections incorporating advanced capabilities.

The rapidly increasing use of digital cameras is causing a corresponding increase in the number and size of personal digital photo collections. There is a corresponding need for powerful tools to help users organize, classify, and browse their collections.

The FXPAL Photo Application is designed to facilitate the organization of digital images from digital cameras and other sources through automated organization and intuitive user interfaces.

Features of the FXPAL Photo Application include:

  • Imported photos are automatically split into time-based events using novel temporal clustering algorithms and optionally integrating location information.
  • Photos can be labeled within a variety of category types (Dates, Events, People, Places, Labels ) and the photos icons in the lighttable can be sorted by any category type.
  • A calendar view of the photos provides an intuitive way of finding photos for a particular date.
  • Integrated face detection and recognition functionality.
  • Automatically generates stained glass collages and animated “pan-n-scan” slideshows” such as the example below.

Technical Contact

Related Publications

2011
Publication Details
  • ACM Multimedia 2011
  • Nov 28, 2011

Abstract

Close
This paper describes methods for clustering photos that include both time stamps and location coordinates. We present versions of a two part method that first detects clusters using time and location information independently. These candidate clusters partition the set of time-ordered photos. A subset of the candidate clusters is selected by an efficient dynamic programming procedure to optimize a cost function. We propose several cost functions to design clusterings that are coherent in space, time, or both. One set of cost functions minimizes inter-photo distances directly. A second set maximizes an information measure to select clusterings for consistency in both time and space across scale.
2005
Publication Details
  • ACM Transactions on Multimedia Computing, Communications, and Applications
  • Aug 8, 2005

Abstract

Close
Organizing digital photograph collections according to events such as holiday gatherings or vacations is a common practice among photographers. To support photographers in this task, we present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We present several variants of an automatic unsupervised algorithm to partition a collection of digital photographs based either on temporal similarity alone, or on temporal and content-based similarity. First, inter-photo similarity is quantified at multiple temporal scales to identify likely event clusters. Second, the final clusters are determined according to one of three clustering goodness criteria. The clustering criteria trade off computational complexity and performance. We also describe a supervised clustering method based on learning vector quantization. Finally, we review the results of an experimental evaluation of the proposed algorithms and existing approaches on two test collections.
2004
Publication Details
  • UIST 2004 Companion, pp. 37-38
  • Oct 24, 2004

Abstract

Close
As the size of the typical personal digital photo collection reaches well into the thousands or photos, advanced tools to manage these large collections are more and more necessary. In this demonstration, we present a semi-automatic approach that opportunistically takes advantage of the current state-of-the-art technology in face detection and recognition and combines it with user interface techniques to facilitate the task of labeling people in photos. We show how we use an accurate face detector to automatically extract faces from photos. Instead of having a less accurate face recognizer classify faces, we use it to sort faces by their similarity to a face model. We demonstrate our photo application that uses the extracted faces as UI proxies for actions on the underlying photos along with the sorting strategy to identify candidate faces for quick and easy face labeling.
Publication Details
  • UIST 2004 Companion, pp. 13-14
  • Oct 24, 2004

Abstract

Close
We developed a novel technique for creating visually pleasing collages from photo regions. The technique is called "stained glass" because the resulting collage with irregular shapes is reminiscent of a stained glass window. The collages reuse photos in novel ways to present photos with faces that can be printed, included in Web pages, or shared via email. The poster describes the requirements for creating stained glass visualizations from photos of faces, our approach for creating face stained glass, and techniques used to improve the aesthetics and flexibility of the stained glass generation. Early user feedback with face stained glass have been very positive.
Publication Details
  • Proceedings of the International Workshop on Multimedia Information Retrieval, ACM Press, pp. 99-106
  • Oct 10, 2004

Abstract

Close
With digital still cameras, users can easily collect thousands of photos. We have created a photo management application with the goal of making photo organization and browsing simple and quick, even for very large collections. A particular concern is the management of photos depicting people. We present a semi-automatic approach designed to facilitate the task of labeling photos with people that opportunistically takes advantage of the strengths of current state-of-the-art technology in face detection and recognition. In particular, an accurate face detector is used to automatically extract faces from photos while the less accurate face recognizer is used not to classify the detected faces, but to sort faces by their similarity to a chosen model. This sorting is used to present candidate faces within a user interface designed for quick and easy face labeling. We present results of a simulation of the usage model that demonstrate the improved ease that is achieved by our method.
2003
Publication Details
  • Proc. ACM Multimedia 2003. pp. 364-373
  • Nov 1, 2003

Abstract

Close
We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We present results for the algorithm based solely on temporal similarity, and jointly on temporal and content-based similarity. We also describe a supervised algorithm based on learning vector quantization. Finally, we include experimental results for the proposed algorithms and several competing approaches on two test collections.
Publication Details
  • Proc. IEEE Intl. Conf. on Image Processing
  • Sep 14, 2003

Abstract

Close
We present similarity-based methods to cluster digital photos by time and image content. This approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We describe versions of the algorithm using temporal similarity with and without content-based similarity, and compare the algorithms with existing techniques, measured against ground-truth clusters created by humans.
Publication Details
  • Human-Computer Interaction INTERACT '03, IOS Press, pp. 196-203
  • Sep 1, 2003

Abstract

Close
With digital still cameras, users can easily collect thousands of photos. Our goal is to make organizing and browsing photos simple and quick, while retaining scalability to large collections. To that end, we created a photo management application concentrating on areas that improve the overall experience without neglecting the mundane components of such an application. Our application automatically divides photos into meaningful events such as birthdays or trips. Several user interaction mechanisms enhance the user experience when organizing photos. Our application combines a light table for showing thumbnails of the entire photo collection with a tree view that supports navigating, sorting, and filtering photos by categories such as dates, events, people, and locations. A calendar view visualizes photos over time and allows for the quick assignment of dates to scanned photos. We fine-tuned our application by using it with large personal photo collections provided by several users.