You are here


Using computer vision and machine learning, Vidrovr makes videos searchable like the web


Founded: 2016
Employees: 2
Quick Pitch:


Vidrovr uses computer vision and machine learning while leveraging constraints in specific vertical domains to build automatic systems for indexing videos, allowing them to be tagged and made searchable. We are able to discover who is speaking on screen, the topics that are being discussed, detect scene changes and link to other forms of media online. Vidrovr is a spin off out of the Digital Video and Multimedia Lab at Columbia University.



Dan Morozoff

Dan is a PhD candidate at Columbia University working on machine learning applied to neuroscience. He has published research in computational physics, computer multimedia. He has worked at NASA, and HHMI Janelia.


Joseph Ellis

Joe is a PhD candidate at Columbia University working on video searching and indexing. He has published research in the areas of multimodal information processing, computer vision and machine learning. He has worked at Google, IBM Research, and MITRE.


Know of jobs at this company? List them!

Submit a new job now