Abstract: In examples, an electronic device is provided. The electronic device includes a processor to receive an input image from an image sensor. The processor is also to scale a size of the input image to a programmed size. The processor is also to encode the scaled input image to provide a feature map having a fractional size of the scaled input image. The processor is also to process the feature map according to lite reduced atrous spatial pyramid pooling (LR-ASPP) to provide a LR-ASPP result. The processor is also to decode the LR-ASPP result to provide an image segmentation result.

Abstract: In some examples in accordance with the present description, an electronic device is provided. The electronic device includes an image sensor and a controller. The controller is to receive multiple images from the image sensor including respective foregrounds and backgrounds. The controller is also to segment the respective foregrounds from the backgrounds. The controller is also to combine the backgrounds to form a fused background. The controller is also to receive a new image including a new image foreground and a new image background. The controller is also to segment the new image foreground from the new image background.

Abstract: In some examples in accordance with the present description, an electronic device is provided. The electronic device includes a controller to implement an image segmentation process. The controller is to obtain color information of an image. The controller also is to obtain depth information of the image. The controller also is to determine a depth of a face represented in the color information. The controller also is to segment a foreground of the image from a background of the image according to the color information and the depth information based on the depth of the face.

Abstract: An object tracking device includes a camera with a field of view oriented in a first direction and a mirror with a field of reflection oriented in a second direction. When an object is in a first region in the field of view of the electronic camera, the camera has a direct view of the object and a reflected view of the object from the mirror. A processor coupled with the camera is configured to receive a first image data set and a second image data set from the camera. The first image data set and the second image data set each include the direct view of the object and the reflected view of the object from the mirror.

Abstract: Embodiments of the present invention provide a novel system and/or method for performing over-the-network collaborations and interactions between remote end-users. Embodiments of the present invention produce the perceived effect of each user sharing a same physical workspace while each person is actually located in separate physical environments. In this manner, embodiments of the present invention allow for more seamless interactions between users while relieving them of the burden of using common computer peripheral devices such as mice, keyboards, and other hardware often used to perform such interactions.

Abstract: Embodiments of the present invention provide a novel system and/or method for performing over-the-network collaborations and interactions between remote end-users. Embodiments of the present invention produce the perceived effect of each user sharing a same physical workspace while each person is actually located in separate physical environments. In this manner, embodiments of the present invention allow for more seamless interactions between users while relieving them of the burden of using common computer peripheral devices such as mice, keyboards, and other hardware often used to perform such interactions.

Abstract: An apparatus comprises a processor configured to: process, automatically and in real time, segmentation of a video object from a portion of a video, wherein the video object is a foreground of the video, and wherein a remaining portion of the video is a background of the video; and remove the background.

Abstract: An apparatus comprises a processor configured to: process, automatically and in real time, segmentation of a video object from a portion of a video, wherein the video object is a foreground of the video, and wherein a remaining portion of the video is a background of the video; and remove the background.

Abstract: An object tracking device includes a camera with a field of view oriented in a first direction and a mirror with a field of reflection oriented in a second direction. When an object is in a first region in the field of view of the electronic camera, the camera has a direct view of the object and a reflected view of the object from the mirror. A processor coupled with the camera is configured to receive a first image data set and a second image data set from the camera. The first image data set and the second image data set each include the direct view of the object and the reflected view of the object from the mirror.

Abstract: Provided is a technology which can prevent deterioration of image quality when enhancing resolution of a predetermined key frame in a video sequence. Specifically, an apparatus to enhance resolution of a video frame is provided. The apparatus includes a frame extraction unit which extracts a key frame and one or more neighboring frames of the key frame from a video sequence; an upsampling unit which upsamples the key frame and the neighboring frames; a motion-vector search unit which calculates a motion vector of the upsampled key frame using the upsampled neighboring frames as reference frames; and a key-frame estimation unit which enhances quality of the upsampled key frame using temporal information obtained from the motion vector and spatial information in the key frame.

Abstract: Provided is a technology which can prevent deterioration of image quality when enhancing resolution of a predetermined key frame in a video sequence. Specifically, an apparatus to enhance resolution of a video frame is provided. The apparatus includes a frame extraction unit which extracts a key frame and one or more neighboring frames of the key frame from a video sequence; an upsampling unit which upsamples the key frame and the neighboring frames; a motion-vector search unit which calculates a motion vector of the upsampled key frame using the upsampled neighboring frames as reference frames; and a key-frame estimation unit which enhances quality of the upsampled key frame using temporal information obtained from the motion vector and spatial information in the key frame.