Abstract: The disclosure relates to system and method for generating recommendations for capturing images of a real-life object with essential features. The method includes detecting an Augmented Reality (AR) plane for a target object. The method further includes capturing a set of poses corresponding to the target object and a set of coordinate points in the AR plane. The set of poses includes a tracking marker, and the set of coordinate points indicates a location of the target object. The method further includes determining an instant distance between the AR imaging device and the target object, and an instant angle of the AR imaging device with respect to the target object. The method further includes dynamically generating the recommendations for adjusting a position and an orientation of the AR imaging device with respect to the target object.

Abstract: The disclosure relates to system and method for providing assistance to a user using augmented reality. The method includes acquiring a video stream and a set of data associated with a task being performed by a user, in real-time, using a camera and/or a sensor device. The video stream includes sequential frames. The method further includes determining a present state associated with the task based on the sequential frames using an Artificial Neural Network (ANN) based action prediction model; determining scenarios and events corresponding to the scenarios based on the video stream and the set of data using an ANN based augmented intelligence model; and determining sequential instructions required for assisting the user to accomplish the task, dynamically, based on the present state and the events associated with the task, using at least one of a rule-based engine and an ANN based instruction prediction model.

Abstract: A method and a system for Augmented Reality (AR) content creation is disclosed. The method includes creating a feature vector corresponding to each of a sequence of frames extracted from a video, based on a plurality of features captured. The method further includes determining a vector distance between each of two consecutive frames from the sequence of frames, based on the feature vector associated with each of the two consecutive frames. The method further includes dividing the video into a plurality of frames based on the determined vector distance. The method further includes creating a storyline based on an object and an action associated with the object in each of the plurality of frames, and generating a set of instructions for a user based on the storyline created for each of the plurality of frames and real-time video stream capturing a current state of a user environment.

Abstract: The disclosure relates to system and method for providing assistance to a user using augmented reality. The method includes acquiring a video stream and a set of data associated with a task being performed by a user, in real-time, using a camera and/or a sensor device. The video stream includes sequential frames.

Abstract: The present invention relates to a method of generating a facial expression of a user for a virtual environment. The method comprises obtaining a video and an associated speech of the user. Further, extracting in real-time at least one of one or more voice features and one or more text features based on the speech. Furthermore, identifying one or more phonemes in the speech. Thereafter, determining one or more facial features relating to the speech of the user using a pre-trained second learning model based on the one or more voice features, the one or more phonemes, the video and one or more previously generated facial features of the user. Finally, generating the facial expression of the user corresponding to the speech for an avatar representing the user in the virtual environment.

Abstract: A method and a system for Augmented Reality (AR) content creation is disclosed. The method includes creating a feature vector corresponding to each of a sequence of frames extracted from a video, based on a plurality of features captured. The method further includes determining a vector distance between each of two consecutive frames from the sequence of frames, based on the feature vector associated with each of the two consecutive frames. The method further includes dividing the video into a plurality of frames based on the determined vector distance. The method further includes creating a storyline based on an object and an action associated with the object in each of the plurality of frames, and generating a set of instructions for a user based on the storyline created for each of the plurality of frames and real-time video stream capturing a current state of a user environment.

Abstract: The disclosure relates to system and method for detecting an instance of lie using a Machine Learning (ML) model. In one example, the method may include extracting a set of features from an input data received from a plurality of data sources at predefined time intervals and combining the set of features from each of the plurality of data sources to obtain a multimodal data. The method may further include processing the multimodal data through an ML model to generate a label for the multimodal data. The label is generated based on a confidence score of the ML model. The label is one of a true value that corresponds to an instance of truth or a false value that corresponds to an instance of lie.

Abstract: The present invention discloses a method and a system for rendering content in low light condition for field assistance. The method comprising receiving real-time input data from a user device in a low light condition, identifying at least one object from the real-time input data and corresponding operational state of the at least one object based on a correlation of the at least one object in the input data and corresponding operational state of the at least object with pre-stored objects and corresponding operational state of the pre-stored objects, predicting at least one action to be performed on the identified at least one object, extracting an Augmented Reality (AR) object associated with the identified at least one object on which the selected action is to be performed, and rendering the location, the selected at least one action to be performed, and the AR object on the user device.

Abstract: The present invention relates to a method of generating a facial expression of a user for a virtual environment. The method comprises obtaining a video and an associated speech of the user. Further, extracting in real-time at least one of one or more voice features and one or more text features based on the speech. Furthermore, identifying one or more phonemes in the speech. Thereafter, determining one or more facial features relating to the speech of the user using a pre-trained second learning model based on the one or more voice features, the one or more phonemes, the video and one or more previously generated facial features of the user. Finally, generating the facial expression of the user corresponding to the speech for an avatar representing the user in the virtual environment.

Abstract: A method and driver assistance system for generating touch-based alerts to a driver in a vehicle is disclosed. The driver assistance system receives frames including the driver in vehicle and detects position of face of the driver in plurality of frames. Facial attributes of the driver are identified based on position of the face and one or more eye attributes of the driver are determined based on the identified one or more facial attributes. Based on the facial attributes and the one or more eye attribute sensory information is estimated from a plurality of sensory data. Further, information regarding haptic sensation is computed for the driver based on estimated sensory information and a position of hands of the driver received from a hand tracking device. Thereafter, an alert is generated using signals relating to the haptic sensation to the driver for taking one or more corrective measure.

Abstract: The present invention discloses a method and a system for rendering content in low light condition for field assistance. The method comprising receiving real-time input data from a user device in a low light condition, identifying at least one object from the real-time input data and corresponding operational state of the at least one object based on a correlation of the at least one object in the input data and corresponding operational state of the at least object with pre-stored objects and corresponding operational state of the pre-stored objects, predicting at least one action to be performed on the identified at least one object, extracting an Augmented Reality (AR) object associated with the identified at least one object on which the selected action is to be performed, and rendering the location, the selected at least one action to be performed, and the AR object on the user device.

Abstract: The disclosure relates to system and method for detecting an instance of lie using a Machine Learning (ML) model. In one example, the method may include extracting a set of features from an input data received from a plurality of data sources at predefined time intervals and combining the set of features from each of the plurality of data sources to obtain a multimodal data. The method may further include processing the multimodal data through an ML model to generate a label for the multimodal data. The label is generated based on a confidence score of the ML model. The label is one of a true value that corresponds to an instance of truth or a false value that corresponds to an instance of lie.

Abstract: A method and driver assistance system for generating touch-based alerts to a driver in a vehicle is disclosed. The driver assistance system receives frames including the driver in vehicle and detects position of face of the driver in plurality of frames. Facial attributes of the driver are identified based on position of the face and one or more eye attributes of the driver are determined based on the identified one or more facial attributes. Based on the facial attributes and the one or more eye attribute sensory information is estimated from a plurality of sensory data. Further, information regarding haptic sensation is computed for the driver based on estimated sensory information and a position of hands of the driver received from a hand tracking device. Thereafter, an alert is generated using signals relating to the haptic sensation to the driver for taking one or more corrective measure.