The main research lines within the Textual and Visual Pattern Analysis (TVPA) area at XRCE are categorization and retrieval of text and images; multimodal and hybrid pattern analysis (text, images, cross-lingual); image clustering and visualization; machine learning; document object detection and image aesthetics. Much of our research along these lines has been delivered into innovative solutions with proven scientific and commercial performance. Examples of this are Xerox GVC (image categorization engine), CategoriX (text categorization engine) and Xerox AIE (Automatic Image Enhancement).

The success of the above topics combined with perceptual user interfaces can allow seamless human-machine interaction. In this context, our aim is to enhance the user experience on navigating through information. This project is part of PinView (Personal Information Navigator through VIEWing), an EU project with partners of six institutions from four EU countries. In particular, the successful candidate will do research in Computer Vision to contribute to our image categorisation system. The goal is to make it more robust on distinguishing between similar categories of images. A proactive system should be designed as a project-wide goal. More specifically, the use of eye gaze tracking paths will be investigated.

The successful candidate will combine competences in C/C++, MatLab, and background in Computer Vision, Pattern Recognition and Machine Learning.

XRCE provides an informal and relaxed working environment situated in the Parc de Maupertuis in Meylan. The successful students will be given the freedom and flexibility to find their own solutions and to work in a way that suits them but will have the guidance and support of experienced full-time Xerox researchers and thereby gain an introduction to the field of commercial research in a world-class research laboratory.