Abstract: This disclosure relates generally to a method and a system for frame stitching based image construction for an indoor environment. The method enables constructing an image of a scene by stitching a plurality of key frames identified from a plurality of image frames captured by a mobile imaging device. The method overcomes multiple challenges posed by the indoor environment, effectively providing clean stitching of the key frames to construct the image of the scene. The method provides image stitching approach that combines visual data from the mobile imaging device and an inertial sensor from an Inertial Measurement Unit (IMU) mounted on the mobile imaging device, with a feedback for error correction to generate robust stitching outputs in indoor scenario.

Abstract: The disclosure herein generally relate to scene change detection, and, more particularly, to use of Unmanned Vehicle (UV) to inspect a scene and perform a scene change detection using UVs. When a UV performs visual inspection of an area or an object, due to various factors, such as but not limited to environmental factors, and movement of object and/or the UV, image of the area/object captured by the drone lacks clarity, which in turn makes detection of any object a difficult task. The UV disclosed herein uses a multi scale super pixel technique for visual change detection, in order to solve the aforementioned issues. In an embodiment, the UV captures an image, identifies a reference image that matches the captured image, and generates a change map. The multi-scale super pixel analysis is then performed on this change map to detect changes between the captured image and the reference image.

Abstract: This disclosure relates generally to inventory management, and more particularly to system and method for airborne shelf inspection and inventor management. When a UAV has to be navigated based on navigation information embedded in visual markers on different items in the inventory, and if one or more of the visual markers are not completely visible due to occlusion, then the UAV automatically recovers data that is missing due to the occlusion, and accordingly navigates the UAV.

Abstract: A system for identification of one or more neuro-cardiological disturbances of a subject in a post-acute stroke treatment and in the intensive care setting is provided. The system includes a wearable device configured for capturing data associated with a neural and heart activity. The wearable device includes a first electrode and a second electrode configured for measuring an electrical activity of a heart to generate a first signal. The wearable device also includes an accelerometer configured for detecting and acquiring neural accelerometry data to generate a second signal. Moreover, the system includes a processor with a memory.

Abstract: A system and method for identifying real time change in a scene of an unknown environment using an unmanned vehicle. In the context of unmanned vehicle navigation, it is critical to calculate the saliency map in real time and employ them in scene understanding. This will reduce the search space and ensure that the process is quicker. A domain specific ontology is created and a saliency model is developed. The saliency model detects key domain specific regions of interest in two consecutive images. The regions of interest is used for registration and change detection. The system is detecting the change by using visual saliency as an abstract feature that is developed in the environment. Probability of change is derived using the salient maps of the two images.

Abstract: This disclosure relates generally to inventory management, and more particularly to system and method for airborne shelf inspection and inventor management. When a UAV has to be navigated based on navigation information embedded in visual markers on different items in the inventory, and if one or more of the visual markers are not completely visible due to occlusion, then the UAV automatically recovers data that is missing due to the occlusion, and accordingly navigates the UAV.

Abstract: System and method for monitoring motor recovery in a post-stroke treatment is disclosed. Motor activity data corresponding to limbs movement is collected during an acute stroke period. The motor activity data is transmitted to at least one base station and an activity value for each arm of two arms is calculated in a predefined time window by using the motor activity data. The activity value for each arm is compared thus providing the monitoring of the motor activity.