Online Video Characteristics and Transcoding Time Dataset

The dataset contains a million randomly sampled video instances listing 10 fundamental video characteristics along with the YouTube video ID. The presented dataset is composed of two tsv files named 'youtube_videos.tsv' and 'transcoding_mesurment.tsv'. The first contains 10 columns of fundamental video characteristics for 1.6 million youtube videos; It contains YouTube video id, duration, bitrate(total in Kbits), bitrate(video bitrate in Kbits), height(in pixle), width(in pixles), framrate, estimated framerate, codec, category, and direct video link. This dataset can be used to gain insight in characteristics of consumer videos found on UGC(Youtube). The second file of our dataset contains 20 columns(see column names for names) which include input and output video characteristics along with their transcoding time and memory resource requirements while transcoding videos to diffrent but valid formats. The second dataset was collected based on experiments on an Intel i7-3720QM CPU through randomly picking two rows from the first dataset and using these as input and output parameters of a video transcoding application, ffmpeg 4 . In section 6 we will use the second dataset to build a transcoding time prediction model and show the significance of our datasets.