156 resultados para Motion perception.
Resumo:
We test Slobin's (2003) Thinking-for-Speaking hypothesis on data from different groups of Turkish-German bilinguals, those living in Germany and those who have returned to Germany.
Resumo:
An algorithm for tracking multiple feature positions in a dynamic image sequence is presented. This is achieved using a combination of two trajectory-based methods, with the resulting hybrid algorithm exhibiting the advantages of both. An optimizing exchange algorithm is described which enables short feature paths to be tracked without prior knowledge of the motion being studied. The resulting partial trajectories are then used to initialize a fast predictor algorithm which is capable of rapidly tracking multiple feature paths. As this predictor algorithm becomes tuned to the feature positions being tracked, it is shown how the location of occluded or poorly detected features can be predicted. The results of applying this tracking algorithm to data obtained from real-world scenes are then presented.
Resumo:
Automatically extracting interesting objects from videos is a very challenging task and is applicable to many research areas such robotics, medical imaging, content based indexing and visual surveillance. Automated visual surveillance is a major research area in computational vision and a commonly applied technique in an attempt to extract objects of interest is that of motion segmentation. Motion segmentation relies on the temporal changes that occur in video sequences to detect objects, but as a technique it presents many challenges that researchers have yet to surmount. Changes in real-time video sequences not only include interesting objects, environmental conditions such as wind, cloud cover, rain and snow may be present, in addition to rapid lighting changes, poor footage quality, moving shadows and reflections. The list provides only a sample of the challenges present. This thesis explores the use of motion segmentation as part of a computational vision system and provides solutions for a practical, generic approach with robust performance, using current neuro-biological, physiological and psychological research in primate vision as inspiration.
Resumo:
Readers need to easily discriminate between different letters, so typefaces are designed to make these differences distinctive. But there is also a uniformity of style within a typeface. These styles are recognised by typographic designers and may be categorised to enable more efficient discrimination among typefaces. The manner in which designers perceive typefaces is explored using the paradigm of Categorical Perception (CP). A continuum of fonts is created by interpolating between two typefaces and two tasks (identification and discrimination) are used to test for CP. As the application of CP to typefaces is a new approach, various methodological issues are pursued. The experiments reveal that the conditions required to demonstrate CP are quite specific and CP was only evident in Times and Helvetica and not Garamond and Bodoni. Possible reasons for this difference are the characteristics of the two typefaces and their context of use. Speculation as to the purpose of CP in non-designers raises the under-researched question of how we identify letters in different typefaces when reading.