Image and Video Aesthetics

Citation Author(s):
Submitted by:
Madhura Phatak
Last updated:
Sat, 10/23/2021 - 05:03
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Datasets for image and video aesthetics

1. Video Dataset : 107 videos This dataset has videos that can be framed into images.

Color contrast,Depth of Field[DoF],Rule of Third[RoT] attributes

that affect aesthetics can be extracted from the video datasets.


2.Slow videos and Fast videos can be assessed for motion

affecting aesthetics


Due to the rise in the popularity of digital cameras and digital photography, there are huge volumes of visual dataavailable on the web. Some of these visual pictures are very beautiful and aesthetically pleasing while the others are not soappealing. Photo aesthetics is an emerging field of research which can categorize large image collections into aesthetically goodand bad photographs. In our paper we discuss the existing aesthetic image evaluation on the basis of: 1) low level attributes e.g.color, texture, edges 2) Middle level attributes e.g., contours, shapes and regions. 3) High level attributes e.g. image composition,image content and sky attributes. We discuss image retrieval with respect to the relationships between the high, middle and lowlevel attributes to reduce the semantic gap between the high level semantic features and low level attributes .Image aesthetics is ahigh level image retrieval attribute, we discuss and analyze the various aesthetics classification and prediction methods prevalentfor determining the aesthetic inclination of an image.Keywords: Photo aesthetics, aesthetic image evaluation, low level attributes, middle level attributes, high level attributes, imageretrieval, semantic gap



Submitted by Asya Turhal on Fri, 10/29/2021 - 10:17