Vidrovr develops multimodal computer vision and machine learning systems to index, tag and understand video. We leverage patented supervised and unsupervised techniques to process videos with specific domain constraints, such as in sports, government and media verticals. We believe true value is generated by building systems that leverage various modalities present in video (pixels, audio and text). Currently, we are working with large media corporations to process their video collections.
Search an indexed video corpus and retrieve content inside videos and link it to other media: photos and text.
Pull out real entities, such as people and organizations out of video streams, articles and images. This is not your old fashioned text search.
Link multimedia content to real news events. See how your and your friends lives are part of the world.
Integrating social media, in order to enable direct interactions between multimedia content. Know when the news affects you and your friends.
Have a great idea how to use our system-- feel free to connect to our APIs. Use our system's capabilities to solve your problems.
Stream broadcast news in near realtime. We get interactive content to you as quickly as possible, so that you act on the news.
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.
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.
Shih-Fu Chang is a professor School of Engineering and at Columbia University. His research focuses on multimedia information retrieval, computer vision, and machine learning with a goal to develop intelligent systems that harness information from massive visual data.
Shikha is a masters candidate at Parsons School of Design studying Design and Technology. Her primary area of focus is User Exeprience Design and Interface Design.
Ethan is a Computer Science and Economics-Statistics double major at Columbia University specializing in artificial intelligence. During his free time he likes to read, cook, and participate in the Columbia Debate Society.
Following up on 3 months of being part of the Combine. Vidrovr is selected to receive followup funding for the incubation program.theCombine
The NewsRover team won two major challenges sponsored by New York City Media Lab. In the Combine program sponsored by NYC Economical Development Commission, the team was selected with major funding to identify products and develop business plans impacting the media industry.
The News Rover system was presented at the 2014 NYC Media Lab Annual Summit and won the second place demo prize. Click here to check the article from NYC Media Lab.NYC Media Lab
The News Rover team presented the News Rover system at newsKDD, a KDD workshop at Bloomberg in New York City.
The News Rover system was presented at the November 2013 New York Tech Meetup alongside several other projects out from the academic sector at the beautiful NYU Skirball Center For The Performing Arts. It was exciting to present our revolutionary new way of getting context for your news!NYTM
Work on News Rover presented in part at ACM Multimedia (MM) 2013 won the Multimedia Grand Challenge 1st Place Award in Barcelona, Spain. The work was entitled “Structured Exploration of Who, What, When, and Where in Heterogeneous Multimedia News Sources”.ACM MM 2013