By Paul P. Maglio, Teenie Matlock, Christopher S. Campbell, Shumin Zhai, Barton A. Smith (auth.), Tieniu Tan, Yuanchun Shi, Wen Gao (eds.)
Multimodal Interfaces represents an rising interdisciplinary examine path and has develop into one of many frontiers in laptop technology. Multimodal interfaces objective at effective, handy and usual interplay and conversation among desktops (in their broadest experience) and human clients. they're going to eventually permit clients to engage with desktops utilizing their daily abilities. those lawsuits comprise the papers authorized for presentation on the 3rd foreign convention on Multimodal Interfaces (ICMI 2000) held in Beijing, China on 1416 O ctober 2000. The papers have been chosen from 172 contributions submitted around the globe. each one paper used to be allotted for evaluate to 3 contributors of this system Committee, which consisted of greater than forty best researchers within the box. ultimate judgements of 38 oral papers and forty eight poster papers have been made in keeping with the reviewers’ reviews and the will for a stability of issues. the choice to have a unmarried song convention ended in a aggressive choice strategy and it's very most likely that a few strong submissions should not integrated during this quantity. The papers gathered the following disguise a variety of themes comparable to affective and perceptual computing, interfaces for wearable and cellular computing, gestures and signal languages, face and facial features research, multilingual interfaces, digital and augmented truth, speech and handwriting, multimodal integration and alertness structures. They signify the various most modern growth in multimodal interfaces research.
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Extra info for Advances in Multimodal Interfaces — ICMI 2000: Third International Conference Beijing, China, October 14–16, 2000 Proceedings
The effects of digitizing noise can be minimized by smoothing this histogram with a small filter. A second histogram of the same dimensions, , can be made from all of the pixels of the same image. This second histogram should also be smoothed by the same ✑ ✑ ✧ ★ ✧ ✒ ✪ ✫ ✔ ✚ ✖ ✜ ✘ ✜ ✣ ✚ ✥ ✦ ✣ ✥ ✦ Visual Recognition of Emotional States 43 filter. These two histograms make it possible to obtain the probability that a given pixel has skin color (see  for a derivation of equation 1): ✑ ✒ ✔ ✖ ✜ ✚ ✘ ✣ ✥ (1) ✦ ✬ ✭ ✚ ✯ ✱ ✳ ✴ ✥ ✣ ✜ ✦ ✶ ✫ ✪ ✧ ★ ✧ ✑ ✚ ✜ ✣ ✥ ✦ In order to detect a skin color region we must group skin pixels into a region.
26 Keith Nesbitt 2 Designing Multi-sensory Models of Abstract Data A multi-sensory model is defined as a mapping between the visual, auditory and haptic artifacts of the display (Fig. 1) and the parameters that characterize the abstract data. Display of abstract data visually is well understood in many areas, but many challenges still exist in displaying information effectively to the auditory and haptic domains [2,3]. The basic over-riding principle I use to design the models is that these mappings be are based on real world analogies or metaphors.
This allows auditory monitoring of multiple trading instruments simultaneously. A traditional use of sound in the stock market is the noise from a ticker-tape which displays the rate of trading. A rapid 'tick' indicating greater market action. Pitch could be mapped to price level. A higher pitch indicating higher prices. Sound volume may be mapped to trading volume. Understanding levels of support or resistance in price can be directly mapped as haptic surfaces that the user can feel and push through.