Abstract-This paper presents a saliency-based video object extraction (VOE) framework. The proposed framework aims to automatically extract foreground objects of interest without any user interaction or the use of any training data (i.e., not limited to any particular type of object). To separate foreground and background regions within and across video frames, the proposed method utilizes visual and motion saliency information extracted from the input video. A conditional random field is applied to effectively combine the saliency induced features, which allows us to deal with unknown pose and scale variations of the foreground object (and its articulated parts). Based on the ability to preserve both spatial continuity and temporal consistency in the proposed VOE framework, experiments on a variety of videos verify that our method is able to produce quantitatively and qualitatively satisfactory VOE results.Index Terms-Conditional random field (CRF), video object extraction (VOE), visual saliency.

Weld lines are commonly present within injection-molded plastic components and generally reduce strength. In designing a plastic part, the designer can often vary the wall thicknesses, or move the gate locations to position the weld line, so that its structural loading is minimized. By altering such variables as melt temperature, mold temperature, and packing pressure, slight increases in weld-line integrity can be achieved. These approaches often do not increase the part strength or performance to an acceptable level, resulting in the exclusion of numerous applications for plastic conversion. This study investigated a hot runner system, sequential valve gates, and heat degree, to achieve economical methods for predicting weld-line properties. By calculating melt front temperatures with MoldFlow analysis, we can predict the strength of the weld line according to the definition of " heat degree " , which is the effective cross-sectional area of the melt front multiplied by the temperature gradient. An effective crosssectional area of the melt front is defined as the area of the temperature above the melting point. In contrast to the test result, when the " sum of heat degree " is lower than 1150 mm 2 ° C for PA6 (Mitsubishi 1030J) and 500 mm 2 ° C for polypropylene (PP) (FCFC K1012), the molecules cannot bond adequately at the interface of the melt fronts. Therefore, the mechanical property declines significantly.

In this paper, we propose novel photography recomposition method, which aims at transferring the photography composition of a reference image to an input image automatically. Without any user interaction, our approach first identifies the salient foreground objects or image regions of interest, and the recomposition is performed by solving a graph-matching based optimization task. With additional post-processing step to preserve the locality and boundary information of the recomposed visual components, we can solve the task of photography recomposition without the uses of any prior knowledge on photography or predetermined image aesthetics rules. Experiments on a variety of images, including transferring the photography composition from real photos, sketches or even paintings, would confirm the effectiveness of our proposed method.

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