quarta-feira, 11 de março de 2009

Paper review: Precise Selection for Multi-Touch Screens

Benko, H., Wilson, A. D., and Baudisch, P. 2006. Precise selection techniques for multi-touch screens. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Montréal, Québec, Canada, April 22 - 27, 2006). R. Grinter, T. Rodden, P. Aoki, E. Cutrell, R. Jeffries, and G. Olson, Eds. CHI '06. ACM, New York, NY, 1263-1272.

link

In current touch screens there is a problem related with the precision of the human fingers. Most of the graphic user interfaces are designed for mouse interaction where the pointing device precision is much higher and all control objects on the screen can have a low amount of pixels. Keeping in mind that the most appealing aspect of touch screens is the ability to directly touch an object in order to interact with it, this paper explains several techniques to increase the pixel-accuracy of the interaction. The techniques includes simulate pressure using the area of touch and placing the cursor at the top of the finger. Another is to place the cursor at an offset distance from the finger to reach corners or edges.  Using two fingers they propose a resizable zoom window that can be used to facilitate the selection of objects with fingers. Finally it is proposed a model for a contextual menu. The paper has a good related work about multi-touch prototypes and interfaces and has an extensive study on the behavior of the users with these techniques.


terça-feira, 10 de março de 2009

Preparing a presentation...

Shorts:

I'm preparing a small 10 min talk for the Scientific and Technical Communication class about:

Multi-point interfaces and interaction


I am also writing a short paper for Interact2009


Call for papers : 3AMIGAS


Paper review: Supporting Multi-point Interaction in Visual Workspaces


Shoemaker, G. and Gutwin, C. 2007. Supporting multi-point interaction in visual workspaces. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (San Jose, California, USA, April 28 - May 03, 2007). CHI '07. ACM, New York, NY, 999-1008.

link

This is a paper describing how to interact using multiple controls in a task but using only a single pointing device. The main techniques described include splitting screen when two control points are too far and fisheye context zoom around control points when more precision is needed.
Does not use simultaneous multi-point interaction.

quarta-feira, 4 de março de 2009

Paper Review: Photo-based question answering

Interesting paper with some ideas on how to use images for searching and question answering.

Yeh, T., Lee, J. J., and Darrell, T. 2008. Photo-based question answering. In Proceeding of the 16th ACM international Conference on Multimedia (Vancouver, British Columbia, Canada, October 26 - 31, 2008). MM '08. ACM, New York, NY, 389-398.

This paper describes a three step method for answering photo-based questions. In traditional text-based query systems there are some problems when the questions performed by the user are centered on physical objects with distinct visual attributes. For example in the question “where can I buy this poster?” using text the user has to perform the question and accurately describe the object or image desired. Using photos the user would instead perform the question and submit an image of the desired poster reducing the amount of text required for the query. To answer the query the authors propose a three-layer system architecture. The first, is a template-based QA, where it takes the question and sees if there is a image database associated with it, then tries to find the image on that database. If it fails the information retrieval layer searches an internal repository to find similar questions already answered. If all fails the last layer answers the query using human-computation using experts or voluntary users feeding the result to the IR layer. In this work three prototypes are presented, one to do photo-based QA in Flikr other for Yahoo!Answers and a mobile application where the user takes pictures of physical objects and executes a question with the resulting image.