Abstract: In various implementations, a computing device is configured to provide a live preview of salient contours generated on a live digital video feed. In particular, a designer can use a computing device with a camera, such as a smart phone, to view a real-time preview of salient contours generated from edges detected in frames of a live digital video feed prior to capture, thereby eliminating the unpredictability of salient contours generated from a previously captured image. In some implementations, the salient contours are overlaid on a greyscale conversion of the live digital video feed for improved processing and visual contrast. Other implementations modify aspects of edge-detecting or post-processing filters for improved performance on mobile computing devices.

Abstract: A content-creation computing system transforms an input raster graphic into a output vector graphic by applying a customization specific to visual characteristics of the input raster graphic. The content-creation computing system provides the input raster graphic to a customization-identification network having a multi-label classifier. The content-creation computing system generates, with the multi-label classifier, a first probability that a first customization operation is applicable to the input raster graphic and a second probability that a second customization operation is applicable to the input raster graphic, wherein the first probability is greater than the second probability. The content-creation computing system selects the first customization operation as the customization specific to the input raster graphic.

Abstract: In various implementations, a computing device is configured to provide a live preview of salient contours generated on a live digital video feed. In particular, a designer can use a computing device with a camera, such as a smart phone, to view a real-time preview of salient contours generated from edges detected in frames of a live digital video feed prior to capture, thereby eliminating the unpredictability of salient contours generated from a previously captured image. In some implementations, the salient contours are overlaid on a greyscale conversion of the live digital video feed for improved processing and visual contrast. Other implementations modify aspects of edge-detecting or post-processing filters for improved performance on mobile computing devices.

Abstract: In various implementations, a computing device is configured to provide a live preview of salient contours generated on a live digital video feed. In particular, a designer can use a computing device with a camera, such as a smart phone, to view a real-time preview of salient contours generated from edges detected in frames of a live digital video feed prior to capture, thereby eliminating the unpredictability of salient contours generated from a previously captured image. In some implementations, the salient contours are overlaid on a greyscale conversion of the live digital video feed for improved processing and visual contrast. Other implementations modify aspects of edge-detecting or post-processing filters for improved performance on mobile computing devices.

Abstract: A content-creation computing system transforms an input raster graphic into a output vector graphic by applying a customization specific to visual characteristics of the input raster graphic. The content-creation computing system provides the input raster graphic to a customization-identification network having a multi-label classifier. The content-creation computing system generates, with the multi-label classifier, a first probability that a first customization operation is applicable to the input raster graphic and a second probability that a second customization operation is applicable to the input raster graphic, wherein the first probability is greater than the second probability. The content-creation computing system selects the first customization operation as the customization specific to the input raster graphic.

Abstract: In various implementations, a computing device is configured to provide a live preview of salient contours generated on a live digital video feed. In particular, a designer can use a computing device with a camera, such as a smart phone, to view a real-time preview of salient contours generated from edges detected in frames of a live digital video feed prior to capture, thereby eliminating the unpredictability of salient contours generated from a previously captured image. In some implementations, the salient contours are overlaid on a greyscale conversion of the live digital video feed for improved processing and visual contrast. Other implementations modify aspects of edge-detecting or post-processing filters for improved performance on mobile computing devices.

Abstract: In various implementations, a computing device is configured to provide a live preview of salient contours generated on a live digital video feed. In particular, a designer can use a computing device with a camera, such as a smart phone, to view a real-time preview of salient contours generated from edges detected in frames of a live digital video feed prior to capture, thereby eliminating the unpredictability of salient contours generated from a previously captured image. In some implementations, the salient contours are overlaid on a greyscale conversion of the live digital video feed for improved processing and visual contrast. Other implementations modify aspects of edge-detecting or post-processing filters for improved performance on mobile computing devices.

Abstract: In various implementations, a computing device is configured to provide a live preview of salient contours generated on a live digital video feed. In particular, a designer can use a computing device with a camera, such as a smart phone, to view a real-time preview of salient contours generated from edges detected in frames of a live digital video feed prior to capture, thereby eliminating the unpredictability of salient contours generated from a previously captured image. In some implementations, the salient contours are overlaid on a greyscale conversion of the live digital video feed for improved processing and visual contrast. Other implementations modify aspects of edge-detecting or post-processing filters for improved performance on mobile computing devices.