Abstract: A method, non-transitory computer readable medium, and productivity assessment computing device that identifies entities present in frames of a video. Entity movement across the frames is plotted to obtain a trajectory of the entities. Interactions of one or more of the entities in each of the frames are identified. A unique sequence encoding is generated for subtasks performed by each of the entities. One of the subtasks is classified as a waste subtask based on one or more of the interactions corresponding to the one of the subtasks and the trajectory and a type of each of the entities associated with the interactions. The sequence encodings of the one of the subtasks are correlated with a number of frames per second of the video to determine waste duration value(s) for a task and the waste duration value(s) are output.

Abstract: This disclosure relates generally to video analysis, and more particularly to systems and methods for mapping object co-ordinates from a video frame view to real world co-ordinates using perspective transformation. In one embodiment, a processor-implemented video frame coordinate transformation method is disclosed. The method may include obtaining an image from an image capture device and identifying, via one or more hardware processors, an object depicted in the image. Further, the method may include determining image-frame object coordinates for the object, and selecting one of a plurality of coordinate transformation matrices associated with the image capture device, based on the image-frame object coordinates for the object.

Abstract: Systems and methods for providing recommendations to obfuscate an entity context in a sensory environment are described. In one implementation, the method comprises receiving entity data and sensory environment data from a plurality of sources. Further, the method comprises analyzing the entity data to obtain categorized entity data. The categorized entity data comprises a plurality of features indicating characteristics of the entity context. Further, the method comprises analyzing the sensory environment data to obtain categorized sensory environment data. Further, the method comprises determining a correlation score for each of the plurality of features by correlating the categorized entity data and the categorized sensory environment data. Further, the method comprises recommending at least one of the plurality of features, based on the correlation score, to obfuscate the entity context in the sensory environment.

Abstract: A method, non-transitory computer readable medium, and productivity assessment computing device that identifies entities present in frames of a video. Entity movement across the frames is plotted to obtain a trajectory of the entities. Interactions of one or more of the entities in each of the frames are identified. A unique sequence encoding is generated for subtasks performed by each of the entities. One of the subtasks is classified as a waste subtask based on one or more of the interactions corresponding to the one of the subtasks and the trajectory and a type of each of the entities associated with the interactions. The sequence encodings of the one of the subtasks are correlated with a number of frames per second of the video to determine waste duration value(s) for a task and the waste duration value(s) are output.

Abstract: This disclosure relates generally to video analysis, and more particularly to systems and methods for mapping object co-ordinates from a video frame view to real world co-ordinates using perspective transformation. In one embodiment, a processor-implemented video frame coordinate transformation method is disclosed. The method may include obtaining an image from an image capture device and identifying, via one or more hardware processors, an object depicted in the image. Further, the method may include determining image-frame object coordinates for the object, and selecting one of a plurality of coordinate transformation matrices associated with the image capture device, based on the image-frame object coordinates for the object.

Abstract: Systems and methods for providing recommendations to obfuscate an entity context in a sensory environment are described. In one implementation, the method comprises receiving entity data and sensory environment data from a plurality of sources. Further, the method comprises analyzing the entity data to obtain categorized entity data. The categorized entity data comprises a plurality of features indicating characteristics of the entity context. Further, the method comprises analyzing the sensory environment data to obtain categorized sensory environment data. Further, the method comprises determining a correlation score for each of the plurality of features by correlating the categorized entity data and the categorized sensory environment data. Further, the method comprises recommending at least one of the plurality of features, based on the correlation score, to obfuscate the entity context in the sensory environment.