A user of a storage system can upload files for a media asset, which can include a high quality media file and various related files. As part of the upload process, the storage system can extract metadata that describes the media asset. The user can specify one or more lifecycle policies to be applied for storage of the asset, and a rules engine can ensure the application of the one or more policies. The rules engine can also enable the use of simple media processing workflows. A filename hashing approach can be used to ensure that the segments and files for the asset are stored in a relatively random and even distribution across the partitions of the storage system. As part of the lifecycle for the asset, the high quality media file can be moved to less expensive storage once transcoding of the asset or another such action occurs.

An apparatus includes a camera and a processor circuit. The camera may be configured to capture color images in response to visible light and monochrome infrared images in response to infrared light. The processor circuit may be configured to extract color features from the color images and add color to corresponding monochrome features detected in the monochrome infrared images.

An apparatus includes a camera and a processor circuit. The camera may be configured to capture color images in response to visible light and monochrome infrared images in response to infrared light. The processor circuit may be configured to extract color features from the color images and add color to corresponding monochrome features detected in the monochrome infrared images.

Techniques are disclosed for automatic scene detection and character extraction. In one example, audiovisual content with video frames, an audio recording, and timing information is received. A score, based on the frame's visual characteristics, is determined for a first frame and subsequent frames. The first frame's score and subsequent frame's scores are compared to determine if the difference between the scores is above a threshold. When the difference in scores is above a threshold, the subsequent frame is classified as a new scene. The audiovisual content is segmented into scenes and textual characters are identified in at least one frame from each scene. The characters are stored and indexed in a searchable database with the timing information for the scene where the characters were identified. The audio recording is transcribed and the transcribed words are stored and indexed in the searchable database with timing information.

Systems and methods for providing summarization, indexing, and post-processing of a recorded document presentation are provided. The system accesses a structured document and recordings associated with a recorded presentation given using the structured document. The system analyzes, using machine-trained models, the structured document, audio and video recordings, and recording of operations performed during the presentation. The analyzing comprises generating a transcript of the audio recording, determining context of components of the structured document, and deriving context from the video recordings and recording of operations. Based on the analyzing, the system segments the recorded presentation into a plurality of segments and generates an index of the plurality of segments that is used for post-processing.

A data storage device and method for object detection and tagging quality of service based on storage workload are provided. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to receive a plurality of image frames for storage in the memory; identify objects in the plurality of image frames; maintain a map that associates each identified object with image frames of the plurality of images frames that contain the identified object; receive a request for image frames that contain an object of interest; and use the map to identify which image frames of the plurality of image frames are associated with the object of interest. Other embodiments are provided.

A data storage device and method for object detection and tagging quality of service based on storage workload are provided. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to receive a plurality of image frames for storage in the memory; identify objects in the plurality of image frames; maintain a map that associates each identified object with image frames of the plurality of images frames that contain the identified object; receive a request for image frames that contain an object of interest; and use the map to identify which image frames of the plurality of image frames are associated with the object of interest. Other embodiments are provided.

Automated product identification within hosted and streamed videos is performed based on video content of a video received at an online video platform and text content associated with the video. First embeddings representative of one or more first candidate products are determined based on video content of the video, such as one or more frames selected from within the video. Second embeddings representative of one or more second candidate products are determined based on text content associated with the video, such as a title, description, or transcript of the video. A product candidate index is produced based on the second embeddings. A product identification representative of a product featured in the video is determined based on a comparison of the first embeddings against entries of the product candidate index, such as including by a nearest neighbor search responsive to the comparison. An indication of the product identification is then output at the online video platform.

Automated product identification within hosted and streamed videos is performed based on video content of a video received at an online video platform and text content associated with the video. First embeddings representative of one or more first candidate products are determined based on video content of the video, such as one or more frames selected from within the video. Second embeddings representative of one or more second candidate products are determined based on text content associated with the video, such as a title, description, or transcript of the video. A product candidate index is produced based on the second embeddings. A product identification representative of a product featured in the video is determined based on a comparison of the first embeddings against entries of the product candidate index, such as including by a nearest neighbor search responsive to the comparison. An indication of the product identification is then output at the online video platform.

Systems and methods for editing a media composition from media assets are provided. An editing device receives a media asset associated with a scene to be rendered in a media composition. The editing device receives a script including script elements that index script sections associated with the scene and metadata. The editing device edits the media composition with segments of the media asset based on a comparison of the segments, the script elements, and the metadata.