CHINA TOPIX

11/02/2024 01:17:07 pm

Make CT Your Homepage

Carved Shells Used To Replicate 1,000-Year-Old Famous Chinese Painting

Qingming Festival by the Riverside

(Photo : Internet Photo) Qingming Festival by the Riverside, a famous ancient painting by artist Zhang Zeduan.

A famous ancient painting has been a source of inspiration for most artists in China and beyond.

The 1,000-year-old painting known as Qingming Festival by the Riverside is a realistic painting showing the happy life of Chinese society during the Northern Song Dynasty. The painting shows more than 500 people, 20 wooden boats and about 60 different animals. Furthermore, it shows around 30 rooms and pavilions with around 20 different vehicles.

Like Us on Facebook

To revive the painting using another medium, craftsman Liu Miaoling and her colleagues used shells. The 50-year old artist and her companions created the 16-meter long shell version of the painting. Liu said it took them around 3 years to finish the project with more than 10 people working on it.

During an interview with China Daily, Liu interpreted the shell-carved picture. She asked the reporter what the man wearing purple was doing. She guessed that the man could have been a food stand owner who was trying to convince another man in pink to sit down. Liu chuckled while making her guesses and said the man in pink along with his friend wanted to take a look on the other side.

The report went on saying Liu has considered every type of shell she is supposed to use to re-make the famous painting. She said she would ask herself several questions before picking out the right shells. Furthermore, she said colors, thickness and shapes were taken into consideration before using it.

For instance, Liu used clamperl for the glazed roofing. Clamperl is a kind of gradual color changing shell. It changes its color to yellow and white from its original black color. Liu also confirmed using a total of 20 types of shells. She said that some of the shells used came from other countries.

Real Time Analytics