Abstract: An artificial intelligence (AI) based method for calibration of a gaming ecosystem and to maximize satisfaction of a player involved in a gaming session such as single-player gaming session, multi-player online gaming session, and a videogame recommendation system is provided. The system detects the gaming session that includes an execution of a video game for a first gameplay and acquires sensor data associated with a player involved in the first gameplay. The sensor data corresponds to a duration of the detected gaming session. The system determines one or more indicators of a dissatisfaction of the player with the first gameplay based on application of one or more Artificial Intelligence (AI) models on the sensor data. The system controls the execution of the video game to modify one or more aspects associated with the first gameplay or a second gameplay of the video game that is different from the first gameplay.

Abstract: An artificial intelligence (AI) based method for calibration of a gaming ecosystem and to maximize satisfaction of a player involved in a gaming session such as single-player gaming session, multi-player online gaming session, and a videogame recommendation system is provided. The system detects the gaming session that includes an execution of a video game for a first gameplay and acquires sensor data associated with a player involved in the first gameplay. The sensor data corresponds to a duration of the detected gaming session. The system determines one or more indicators of a dissatisfaction of the player with the first gameplay based on application of one or more Artificial Intelligence (AI) models on the sensor data. The system controls the execution of the video game to modify one or more aspects associated with the first gameplay or a second gameplay of the video game that is different from the first gameplay.

Abstract: A compressed light field imaging system is described. The light field 3D data is analyzed to determine optimal subset of light field samples to be (acquired) rendered, while the remaining samples are generated using multi-reference depth-image based rendering. The light field is encoded and transmitted to the display. The 3D display directly reconstructs the light field and avoids data expansion that usually occurs in conventional imaging systems. The present invention enables the realization of full parallax 3D compressed imaging system that achieves high compression performance while minimizing memory and computational requirements.

Abstract: A compressed light field imaging system is described. The light field 3D data is analyzed to determine optimal subset of light field samples to be (acquired) rendered, while the remaining samples are generated using multi-reference depth-image based rendering. The light field is encoded and transmitted to the display. The 3D display directly reconstructs the light field and avoids data expansion that usually occurs in conventional imaging systems. The present invention enables the realization of full parallax 3D compressed imaging system that achieves high compression performance while minimizing memory and computational requirements.

Abstract: Image compression methods for near-eye display systems that reduce the input bandwidth and the system processing resource are disclosed. High order basis modulation, dynamic gamut, light field depth sampling and image data word-length truncation and quantization aiming at matching the human visual system angular, color and depth acuity coupled with use of compressed input display enable a high fidelity visual experience in near-eye display systems suited for mobile applications at a substantially reduced input interface bandwidths and processing resources.

Abstract: Preprocessing of the light field input data for full parallax compressed light field 3D display systems is described. The described light field input data preprocessing can be utilized to format or extract information from input data, which can then be used by the light field compression system to further enhance the compression performance, reduce processing requirements, achieve real-time performance and reduce power consumption. This light field input data preprocessing performs a high-level 3D scene analysis and extracts data properties to be used by the light field compression system at different stages. As a result, rendering of redundant data is avoided while at the same rendering quality is improved.

Abstract: A compressed light field imaging system is described. The light field 3D data is analyzed to determine optimal subset of light field samples to be (acquired) rendered, while the remaining samples are generated using multi-reference depth-image based rendering. The light field is encoded and transmitted to the display. The 3D display directly reconstructs the light field and avoids data expansion that usually occurs in conventional imaging systems. The present invention enables the realization of full parallax 3D compressed imaging system that achieves high compression performance while minimizing memory and computational requirements.

Abstract: A method interpolates and filters a depth image with reduced resolution to recover a high resolution depth image using edge information, wherein each depth image includes an array of pixels at locations and wherein each pixel has a depth. The reduced depth image is first up-sampled, interpolating the missing positions by repeating the nearest-neighboring depth value. Next, a moving window is applied to the pixels in the up-sampled depth image. The window covers a set of pixels centred at each pixel. The pixels covered by the window are selected according to their relative offset to the depth edge, and only pixels that are within the same side of the depth edge of the centre pixel are used for the filtering procedure.