Animating digital characters has an important role in computer assisted experiences, from video games to movies to interactive robotics. A critical challenge in the field is to generate animations which accurately reflect the state of the animated characters, without looking repetitive or unnatural. In this work, we investigate the problem of procedurally generating a diverse variety of facial animations that express a given semantic quality (e.g., very happy). To that end, we introduce a new learning heuristic called Precision Variety Learning (PVL) which actively identifies and exploits the fundamental trade-off between precision (how accurate positive labels are) and variety (how diverse the set of positive labels is). We both identify conditions where important theoretical properties can be guaranteed, and show good empirical performance in variety of conditions. Lastly, we apply our PVL heuristic to our motivating problem of generating smile animations, and perform several user studies to validate the ability of our method to produce a perceptually diverse variety of smiles for different target intensities.
This study developed a web-based text editor to eliminate the incompatibility of computer keyboard with the three major indigenous languages in Nigeria. It also aims to reduce the time taken to produce characters with diacritical marks. The editors produced valid Unicode characters and require pressing less buttons to generating all the symbols of the alphabets for the three major indigenous languages in Nigeria. Client-side technologies were used to develop these applications. Three web pages, designated for Yorùbá, Igbo and Hausa language were generated with HTML. CSS was used to define the look and feel of the HTML elements on each page. Regular Expressions implemented in JavaScript functions were used to convert selected ASCII characters into desired Unicode characters. The editors are available at http://www.gazaliwakil.com.ng. The editors work well on latest version of browsers like (Google Chrome, Mozilla Firefox, Opera, and Internet Explorer). They are very light, consume minimal server resources and can work offline. The system was launched Fifty-one (51) times to extract data comprising the Loading, Scripting, Rendering, Painting, System, and Idle time. The obtained result showed that on the average, it takes about 13.77ms to load the HTML DOM elements, 42.83ms to load the javaScript, 13.10ms and 1.73ms for rendering and painting the page by CSS. Additional time taken are 43.91ms and 3,045.10ms for the system and idle time respectively. A total time of 3,160.43ms (3.16s) is required when any of the editors is launched before the page can accept inputs from the users. It also takes the editors 2.66ms to add diacritical marks on a letter. This would, in effect, not reduce the typing speed of users.
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