Abstract: A system for video segmentation may include a neural network and a memory including multi-range arrays. The multi-range arrays may store feature map arrays including different number of feature maps. The system may generate a feature map from a frame in a video at a time and store the feature map in the memory. The feature map may be in a feature map array that also includes one or more contextual feature maps generated from other frames in the video. The system uses the feature map array to determine whether the frame falls into a segment of the video. The system may generate a new feature map later from another frame and include the new feature map in a new feature map array that also includes the first feature map. The system uses the new feature map array to determine whether the new frame falls into a segment.

Abstract: The application provides an apparatus and a method for procedural video assessment. The apparatus includes: interface circuitry; and processor circuitry coupled to the interface circuitry and configured to: perform an action segmentation process for a procedural video received via the interface circuitry to obtain a plurality of action features associated with the procedure video; transform the plurality of action features into a plurality of action-procedure features based on an action-procedure relationship learning module for discovering a relationship between the plurality of action features and a plurality of scoring oriented procedures associated with the procedure video; and perform a procedure classification process to infer the plurality of scoring oriented procedures from the plurality of action-procedure features.

Abstract: Embodiments of adaptive multi-modal event detection are disclosed herein. In one example, sensor data captured by multiple sensors is received, and an inconsistency among the sensors is detected based on performing event detection on the sensor data. An external environment of the sensors is detected based on the sensor data, and one or more configuration parameter(s) for event detection are adjusted based on the external environment of the sensors. Event detection is then performed on the sensor data based on the adjusted configuration parameter(s).