In today’s world binge watching has become a way of life not just for Gen-Z but also for many baby boomers. Viewers are watching more content than ever. In particular, Over-The-Top (OTT) and Video-On-Demand (VOD) platforms provide a rich selection of content choices anytime, anywhere, and on any screen. With proliferating content volumes, media companies are facing challenges in preparing and managing their content. This is crucial to provide a high-quality viewing experience and better monetizing content. Some of the use cases involved are,
While these approaches were traditionally handled by large team of trained human workforces, many AI based approaches have evolved such as Amazon Rekognition’s video segmentation API. AI models are getting better at addressing above mentioned use cases but they are typically pre-trained on a different types of content and may not be accurate for your content library. So, what if we use AI enabled human in the loop approach to reduce cost and improve accuracy of video segmentation tasks.
In our approach, the AI based APIs can provide weaker labels to detect video segments and send for review to trained human reviewers for creating picture perfect segments. The approach tremendously improves your media content understanding and helps generate ground truth to fine-tune AI models. Below is workflow of end-2-end solution,
Artificial intelligence(AI) has become ubiquitous in Media and Entertainment to improve content understanding to increase user engagement and also drive ad revenue. The AI enabled Human in the loop approach outlined is best of breed solution to reduce the human cost and provide highest quality. The approach can be also extended to other use cases such as content moderation, ad placement and personalized trailer generation.
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