Vidrovr was founded by two PhD Students in the Digital Video and Multimedia Lab at Columbia University, Joseph Ellis ’17CU and Daniel Morozoff ’16CU. The Vidrovr team is advised by Prof. Shih-Fu Chang, of the Columbia School of Engineering and Applied Science. The team has diverse experience in building distributed systems that can process and learn from vast amounts of information in real time, in particular designing algorithms that utilize multiple facets of multimedia streams concurrently.
They have published and patented foundational research in machine learning, computer vision, multimodal information processing, and multimedia. Over the past three years they have developed an award-winning and patented system for processing news videos and social media, called News Rover, and the technologies developed for this system are directly leveraged in Vidrovr products
Vidrovr has currently obtained pre-seed convertible note and grant funding to transition their patented technologies developed at Columbia to provide value searching and indexing the video collections of large media corporations. Vidrovr is currently working with enterprise customers to design products and systems that provide value to news rooms, archivists, and digital product creators.
The company is currently working through pilot programs and developing our cloud based video processing and understanding infrastructure. Vidrovr addresses three key market needs: 1. Domain and customer specific automatic metadata generation for videos, 2. Video Content Management solutions that enable automatic placement and recommendation of video clips for digital products, and 3. Automatically linking and sourcing visual social media content that is relevant to a particular video or online article before it is published.