Abstract: A system and method of object detection are disclosed. In a particular implementation, a method of processing an image includes receiving, at a processor, image data associated with an image of a scene. The scene includes a road region. The method further includes detecting the road region based on the image data and determining a subset of the image data. The subset excludes at least a portion of the image data corresponding to the road region. The method further includes performing an object detection operation on the subset of the image data to detect an object. The object detection operation performed on the subset of the image data is exclusive of the at least a portion of the image data corresponding to the road region.

Abstract: Techniques and systems are provided for processing video data. For example, techniques and systems are provided for performing content-adaptive blob filtering. A number of blobs generated for a video frame is determined. A size of a first blob from the blobs is determined, the first blob including pixels of at least a portion of a first foreground object in the video frame. The first blob is filtered from the plurality of blobs when the size of the first blob is less than a size threshold. The size threshold is determined based on the number of the plurality of blobs generated for the video frame.

Abstract: Techniques and systems are provided for generating a background picture. The background picture can be used for coding one or more pictures. For example, a method of generating a background picture includes generating a long-term background model for one or more pixels of a background picture. The long-term background model includes a statistical model for detecting long-term motion of the one or more pixels in a sequence of pictures. The method further includes generating a short-term background model for the one or more pixels of the background picture. The short-term background model detects short-term motion of the one or more pixels between two or more pictures. The method further includes determining a value for the one or more pixels of the background picture using the long-term background model and the short-term background model.

Abstract: A method of processing data includes receiving, at a computing device, data representative of an image captured by an image sensor. The method also includes determining a first scene clarity score. The method further includes determining whether the first scene clarity score satisfies a threshold, and if the first scene clarity score satisfies the threshold, determining a second scene clarity score based on second data extracted from the data.

Abstract: A system and method of object detection are disclosed. In a particular implementation, a method of processing an image includes receiving, at a processor, image data associated with an image of a scene. The scene includes a road region. The method further includes detecting the road region based on the image data and determining a subset of the image data. The subset excludes at least a portion of the image data corresponding to the road region. The method further includes performing an object detection operation on the subset of the image data to detect an object. The object detection operation performed on the subset of the image data is exclusive of the at least a portion of the image data corresponding to the road region.

Abstract: A method performed by an electronic device is described. The method includes obtaining a combined image. The combined image includes a combination of images captured from one or more image sensors. The method also includes obtaining depth information. The depth information is based on a distance measurement between a depth sensor and at least one object in the combined image. The method further includes adjusting a combined image visualization based on the depth information.

Abstract: A method performed by an electronic device is described. The method includes obtaining a first frame of a scene. The method also includes performing object recognition of at least one object within a first bounding region of the first frame. The method further includes performing object tracking of the at least one object within the first bounding region of the first frame. The method additionally includes determining a second bounding region of a second frame based on the object tracking. The second frame is subsequent to the first frame. The method also includes determining whether the second bounding region is valid based on a predetermined object model.

Abstract: A method of processing data includes receiving, at a computing device, data representative of an image captured by an image sensor. The method also includes determining a first scene clarity score. The method further includes determining whether the first scene clarity score satisfies a threshold, and if the first scene clarity score satisfies the threshold, determining a second scene clarity score based on second data extracted from the data.

Abstract: An apparatus includes an object detector configured to receive image data of a scene viewed from the apparatus and including an object. The image data is associated with multiple scale space representations of the scene. The object detector is configured to detect the object responsive to location data and a first scale space representation of the multiple scale space representations.

Abstract: A method includes accessing, at a computing device, data descriptive of a graph representing a program. The graph includes multiple nodes representing execution steps of the program and includes multiple edges representing data transfer steps. The method also includes determining at least two heterogeneous hardware resources of the computing device that are available to execute code represented by one or more of the nodes, and determining one or more paths from a source node to a sink node based on a topology of the graph. The method further includes scheduling execution of code at the at least two heterogeneous hardware resources. The code is represented by at least one of the multiple nodes, and the execution of the code is scheduled based on the one or more paths.

Abstract: This disclosure describes techniques for modifying application program interface (API) calls in a manner that can cause a device to render native three dimensional (3D) graphics content in stereoscopic 3D. The techniques of this disclosure can be implemented in a manner where API calls themselves are modified, but the API itself and the GPU hardware are not modified. The techniques of the present disclosure include using the same viewing frustum defined by the original content to generate a left-eye image and a right-eye image and shifting the viewport offset of the left-eye image and the right-eye image.

Abstract: A method includes accessing, at a computing device, data descriptive of a graph representing a program. The graph includes multiple nodes representing execution steps of the program and includes multiple edges representing data transfer steps. The method also includes determining at least two heterogeneous hardware resources of the computing device that are available to execute code represented by one or more of the nodes, and determining one or more paths from a source node to a sink node based on a topology of the graph. The method further includes scheduling execution of code at the at least two heterogeneous hardware resources. The code is represented by at least one of the multiple nodes, and the execution of the code is scheduled based on the one or more paths.

Abstract: A computing device configured for providing an interface is described. The computing device includes a processor and instructions stored in memory. The computing device projects a projected image from a projector. The computing device also captures an image including the projected image using a camera. The camera operates in a visible spectrum. The computing device calibrates itself, detects a hand and tracks the hand based on a tracking pattern in a search space. The computing device also performs an operation.

Abstract: This disclosure describes techniques for modifying application program interface (API) calls in a manner that can cause a device to render native three dimensional (3D) graphics content in stereoscopic 3D. The techniques of this disclosure can be implemented in a manner where API calls themselves are modified, but the API itself and the GPU hardware are not modified. The techniques of the present disclosure include using the same viewing frustum defined by the original content to generate a left-eye image and a right-eye image and shifting the viewport offset of the left-eye image and the right-eye image.

Abstract: A computing device configured for providing an interface is described. The computing device includes a processor and instructions stored in memory. The computing device projects a projected image from a projector. The computing device also captures an image including the projected image using a camera. The camera operates in a visible spectrum. The computing device calibrates itself, detects a hand and tracks the hand based on a tracking pattern in a search space. The computing device also performs an operation.