Depth Measurement of Face and Palate by Structured Light

In order to model speech production for purposes such as articulatory synthesis, articulatory data must be acquired, preferably in a way that does not impede the speaker's ability to speak. A variety of techniques has been used, many of them, such as ultrasound, X-rays, or MRI, adapted from medical imaging. For externally accessible articulators such techniques are not appropriate, but the task of measuring the shape of a complex three-dimensional object is still difficult. For a static object such as a dental impression manual methods such as slicing a mold of the impression and measuring the slices with calipers can be quite accurate, though time-consuming. For a dynamic object such as the face shape during speech such manual methods cannot be used. A workable alternative has been developed at Grenoble that instead uses simultaneous video pictures of front and profile face. Blue lipstick is used on the subject's lips to provide a definite outline and provide maximum contrast with the teeth and tongue. The images must then be post-processed before parameters such as mouth area are extracted. In this paper we present a structured light system which uses a slide projector and a single video camera to acquire depth coordinates of a static or moving object. We discuss pilot experiments aimed at optimising its output and establishing its accuracy, and make some preliminary comparisons with the Grenoble double-video system. In the next section the structured light technique is summarised, focusing on the experimental constraints it imposes. The technique is described in more detail elsewhere. In Static measurements' its use on the static object of an EPG palate is described. In 'Dynamic measurements' its use in acquiring dynamic face shape data is described, focusing on methodology issues that arose in an extended recording session with a human speaker. In the discussion we describe the calibration procedure and the related tradeoffs, and finally we make some initial comparisons to the double-video system

Testing a global standard for quantifying species recovery and assessing conservation impact.

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard