Smart camera

About: Smart camera is a research topic. Over the lifetime, 5571 publications have been published within this topic receiving 93054 citations. The topic is also known as: intelligent camera.

System and method for providing depth adaptive video conferencing

Abstract: A method is provided in one example and includes capturing panoramic image data through a first camera in a camera cluster, and capturing close-up image data through a second camera included as part of a spaced array of cameras. The presence of a user in a field of view of the second camera can be detected. The close-up image data and the panoramic image data can be combined to form a combined image. In more specific embodiments, the detecting includes evaluating a distance between the user and the second camera. The combined image can reflect a removal of a portion of panoramic image data associated with the user in a video conferencing environment.

Web inspection system

Abstract: A web inspection system provides detection of web flaws along the machine direction and cross direction of a web. The detectable percent contrast between good web material and bad web material in one embodiment approaches noise level. The web inspection system utilizes a multiple of smart cameras connected to a host computer via an ethernet hub. Each smart camera includes a line scan camera for producing digital pixels, a means for lighting and pixel correction on a pixel by pixel basis, a web edge detector for monitoring the edges of a web, a multi-pipeline flaw detection pre-processor for detecting very small changes in the web material, a run length encoder for generating data regarding the location of each group of potential flaws in a cross direction, a 2D blob detector and analyzer for generating data regarding the location of block flaws along a machine direction, and an inspect/reject analysis for determining the actual flaw data from the potential flaw data. A low contrast web inspection system provides a balanced and distributed architecture that handles high defect rates, and that is easily integrated with an existing web manufacturing system.

Optimal Camera Placement for Automated Surveillance Tasks

Abstract: Camera placement has an enormous impact on the performance of vision systems, but the best placement to maximize performance depends on the purpose of the system. As a result, this paper focuses largely on the problem of task-specific camera placement. We propose a new camera placement method that optimizes views to provide the highest resolution images of objects and motions in the scene that are critical for the performance of some specified task (e.g. motion recognition, visual metrology, part identification, etc.). A general analytical formulation of the observation problem is developed in terms of motion statistics of a scene and resolution of observed actions resulting in an aggregate observability measure. The goal of this system is to optimize across multiple cameras the aggregate observability of the set of actions performed in a defined area. The method considers dynamic and unpredictable environments, where the subject of interest changes in time. It does not attempt to measure or reconstruct surfaces or objects, and does not use an internal model of the subjects for reference. As a result, this method differs significantly in its core formulation from camera placement solutions applied to problems such as inspection, reconstruction or the Art Gallery class of problems. We present tests of the system's optimized camera placement solutions using real-world data in both indoor and outdoor situations and robot-based experimentation using an all terrain robot vehicle-Jr robot in an indoor setting.

Towards vision-based 3-D people tracking in a smart room

Abstract: This paper presents our work on building a real time distributed system to track 3-D locations of people in an indoor environment, such as a smart room, using multiple calibrated cameras. In our system, each camera is connected to a dedicated computer on which foreground regions in the camera image are detected. This is done using an adpative background model. These detected foreground regions are broadcasted to a tracking agent, which computes believed 3-D locations of persons based on the detected image regions. We have implemented both a best-hypothesis heuristic tracking approach as well as a probabilistic multi-hypothesis tracker to find the object tracks from these 3-D locations. The two tracking approaches are evaluated on a sequence of two people walking in a conference room recorded with three cameras. The results suggest that the probabilistic tracker shows comparable performance to the heuristic tracker.

Remote determination of image-acquisition settings and opportunities

Abstract: Pre-image-acquisition information is obtained by a digital camera and transmitted to a system external to the digital camera. The system is configured to provide image-acquisition settings to the digital camera. In this regard, the digital camera receives the image-acquisition settings from the external system and performs an image-acquisition sequence based at least upon the received image-acquisition settings. Accordingly, the determination of image-acquisition settings can be performed remotely from the digital camera, where data-processing resources can greatly exceed those within the digital camera.