Category Archives: Art

South Dakota’s Newest Landmark – “Dignity”

Peter Lobner

When I was in South Dakota last week, a major new landmark was created when the 50-foot tall, stainless steel statue named “Dignity” was installed on a bluff overlooking Chamberlin and the Missouri River. The statue of a young Native American woman with a star quilt was commissioned two years ago with a $1 million gift from Norm and Eunabel McKie of Rapid City, SD and was created by Sturgis, SD artist Dale Lamphere.

DSC_6091 cropPhoto by author.DSC_6082-84 panoPhoto by author.

Lamphere is quoted as saying, “My intent for this is to have the sculpture stand as an enduring symbol of our shared belief that we are in a sacred place and that we are all sacred.”

The star quilt is a traditional symbol of honor among the local Native American Lakota people. You’ll find more information on the star quilt and its symbolism at the following link.

DSC_6078Photo by author.

Standing at the top of the bluff leaves the statue exposed to strong winds that are common in the area. To mitigate the effects of the wind, many of the pieces of the diamond quilt are articulated to allow the wind to pass freely through the stainless steel structure of the quilt.

DSC_6088Photo by author.

At the unveiling ceremony, South Dakota Governor Dennis Daugaard remarked:

“This is very meaningful for our state. In addition to being the state of Mount Rushmore and the state of Crazy Horse, I believe the prominent location of “Dignity” and the visibility she offers to so many millions of travelers who will be moving up and down Interstate 90, I think we’ll soon become not just the state of those two stone monuments, but also this beautiful metal sculpture as well.”

In the current climate of divisiveness that is permeating this nation, “Dignity” stands as a welcome symbol of hopefulness. Thank you, Norm and Eunabel McKie, for your generous gift to the state of South Dakota and to this great nation of ours.

Stunning Ultra High Resolution Images From the Google Art Camera

Peter Lobner

The Google Cultural Institute created the ultra high resolution Art Camera as a tool for capturing extraordinary digital images of two-dimensional artwork. The Institute states:

 “Working with museums around the world, Google has used its Art Camera system to capture the finest details of artworks from their collection.”

A short video at the following link provides a brief introduction to the Art Camera.

The Art Camera simplifies and speeds up the process of capturing ultra high resolution digital images, enabling a 1 meter square (39.4 inch square) piece of flat art to be imaged in about 30 minutes. Previously, this task took about a day using third-party scanning equipment.

The Art Camera is set up in front of the artwork to be digitized, the edges of the image to be captured are identified for the Art Camera, and then the camera proceeds automatically, taking ultra high-resolution photos across the entire surface within the identified edges. The resulting set of digital photos are processed by Google and converted into a single gigapixel file.

Google has built 20 Art Cameras and is lending them out to institutions around the world at no cost to assist in capturing digital images of important art collections.

You can see many examples of artwork images captured by the Art Camera at the following link:

Among the images on this site is the very detailed Chinese ink and color on silk image shown below. The original image measures about 39 x 31 cm (15 x 12 inches). The first image below is of the entire scene. Following are two images that show the higher resolution available as you zoom in on the dragon’s head and reveal the fine details of the original image, including the weave in the silk fabric.

Google cultural Institute image

GCI image detail 1

GCI image detail 2

Image credit, three images above: Google Cultural Institute/The Nelson-Atkins Museum of Art

In the following pointillist painting by Camille Pissarro, entitled Apple Harvest, the complex details of the artist’s brush strokes and points of paint become evident as you zoom in and explore the image. The original image measures about 74 x 61 cm (29 x 24 inches).

Pissaro Apple Harvest

Pissaro image detail 1

Pissaro image detail 2

Image credit, three images above: Google Cultural Institute/Dallas Museum of Art

Hopefully, art museums and galleries around the world will take advantage of Google’s Art Camera or similar technologies to capture and present their art collections to the world in this rich digital format.

A Neural Algorithm of Artistic Style

Peter Lobner

Authors Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge published the subject research paper on 26 Aug 2015 to, “Introduce an artificial system based on a Deep Neural Network that creates artistic images of high perceptual quality.”

Convolutional Neural Networks are a class of Deep Neural Network that is very powerful and well suited for image processing tasks. Common usage is in object and facial recognition systems. The authors explain how their neural algorithm works in a Convolutional Neural Network to independently capture content and style in a composite image that represents the content of an original image in a style derived from an arbitrarily selected second image. The authors state that: “The key finding of this paper is that the representations of content and style in the Convolutional Neural Network are separable. That is, we can manipulate both representations independently to produce new, perceptually meaningful images.”

In their paper, the authors selected the following photo to define the image content.

Neural net pic 1

Two examples of the image selected to define the style, and the resulting final image created by the neural algorithm are shown below.

Style derived from The Starry Night by Vincent van Gogh, 1889.

Neural net pic2

Style derived from Der Schrei by Edvard Munch, 1893

Neural net pic3

I find these results to be simply amazing in terms of their artistic composition and their effective implementation of the selected style.

It probably is premature, but I hope there soon will be a reasonably priced app for this to runs on a Mac or PC. I would buy that app in a heartbeat.

You can download the full paper, which includes all of the examples shown above, from the Cornell University Library at the following link: