Joint segmentation of color and depth data based on splitting and merging driven by surface fitting

This paper proposes a segmentation scheme based on the joint usage of color and depth data together with a 3D surface estimation scheme. Firstly a set of multi-dimensional vectors is built from color, geometry and surface orientation information. Normalized cuts spectral clustering is then applied in order to recursively segment the scene in two parts thus obtaining an over-segmentation. This procedure is followed by a recursive merging stage where close segments belonging to the same object are joined together. At each step of both procedures a NURBS model is fitted on the computed segments and the accuracy of the fitting is used as a measure of the plausibility that a segment represents a single surface or object. By comparing the accuracy to the one at the previous step, it is possible to determine if each splitting or merging operation leads to a better scene representation and consequently whether to perform it or not. Experimental results show how the proposed method provides an accurate and reliable segmentation

Joint segmentation of color and depth data based on splitting and merging driven by surface fitting

This paper proposes a segmentation scheme based on the joint usage of color and depth data together with a 3D surface estimation scheme. Firstly a set of multi-dimensional vectors is built from color, geometry and surface orientation information. Normalized cuts spectral clustering is then applied in order to recursively segment the scene in two parts thus obtaining an over-segmentation. This procedure is followed by a recursive merging stage where close segments belonging to the same object are joined together. At each step of both procedures a NURBS model is fitted on the computed segments and the accuracy of the fitting is used as a measure of the plausibility that a segment represents a single surface or object. By comparing the accuracy to the one at the previous step, it is possible to determine if each splitting or merging operation leads to a better scene representation and consequently whether to perform it or not. Experimental results show how the proposed method provides an accurate and reliable segmentation

Factors affecting color appearance and measurement by psychophysical methods

Chromatic adaptation has been studied by applying methods of direct scaling to color appearances of stimuli perceived under different conditions of adaptation. This study differs from previous work in a number of ways. The color appearances of surface color stimuli were scaled by both magnitude estimation and magnitude production psychophysical methods. Changes in color appearances resulting from variations in correlated color temperature of adapting illumination, luminance factors of samples, illuininance, and surround induction conditions were scaled by a group of seven observers who had been trained to describe their perceptions in a uniform manner. This factorial approach to chromatic adaptation- influences on color appearance has yielded information about changes throughout a color solid rather than a single planar section of that solid. A distinction was made between absolute and relative attributes of color appearance. valuations of both internal and external consistency indicate that the data generated have relatively high precision and validity. The results indicate that chromatic adaptation induces smooth, continuous changes in color appearance. The nature of these changes depends upon correlated color temperature, luminance factor, and illuminance of surface color stimuli. Saturation, or colorfulness, is most susceptible to change and is highly dependent upon luminance factor and illuminance in addition to color temperature. These dependencies are systematic and explicit in the results presented here. Hue appearance of a given sample depends primarily upon color temperature of adapting illumination. Little or no change in hue was found for the range of variation in illuminance and luminance factor included in this study. In general, the hues of' all stimuli change with adaptation but there are important exceptions. The results do not support a linear model for the chromatic adaptation process