Abstract: Systems, methods, and computer-readable media for gesture recognition are disclosed. The systems include, for example, at least one processor that is configured to receive at least one image from at least one image sensor. The processor may also be configured to detect, in the image, data corresponding to an anatomical structure of a user. The processor may also be configured to identify, in the image, information corresponding to a suspected hand gesture by the user. In addition, the processor may also be configured to discount the information corresponding to the suspected hand gesture if the data corresponding to the anatomical structure of the user is not identified in the image.

Abstract: Systems, methods and non-transitory computer-readable media for triggering actions based on touch-free gesture detection are disclosed. The disclosed systems may include at least one processor. A processor may be configured to receive image information from an image sensor, detect in the image information a gesture performed by a user, detect a location of the gesture in the image information, access information associated with at least one control boundary, the control boundary relating to a physical dimension of a device in a field of view of the user, or a physical dimension of a body of the user as perceived by the image sensor, and cause an action associated with the detected gesture, the detected gesture location, and a relationship between the detected gesture location and the control boundary.

Abstract: A system for inputting operation system (OS) commands to a data processing device. The system comprises a video camera that captures images of a viewing space. A processor detects a predetermined object in the images using an object recognition algorithm not involving background information in an image. One or more image analysis parameters of the object are extracted from the images and one or more motion detection tests are applied. Each motion detection test has an associated OS command, and when a test succeeds, the OS command associated with the test is executed. By not relying on background information in an image, the system of the invention may be used in devices that are moved in use, such as a palm plot, personal digital assistant (PDA), a mobile telephone, a digital camera, and a mobile game machine.

Abstract: A system for inputting operation system (OS) commands to a data processing device. The system comprises a video camera that captures images of a viewing space. A processor detects a predetermined object in the images using an object recognition algorithm not involving background information in an image. One or more image analysis parameters of the object are extracted from the images and one or more motion detection tests are applied. Each motion detection test has an associated OS command, and when a test succeeds, the OS command associated with the test is executed. By not relying on background information in an image, the system of the invention may be used in devices that are moved in use, such as a palm plot, personal digital assistant (PDA), a mobile telephone, a digital camera, and a mobile game machine.

Abstract: Provided is a system for inputting operation system (OS) commands to a data processing device. The system includes a video camera that captures images of a viewing space. A processor detects a predetermined object in the images using an object recognition algorithm not involving background information in an image. One or more image analysis parameters of the object are extracted from the images and one or more motion detection tests are applied. Each motion detection test has an associated OS command, and when a test succeeds, the OS command associated with the test is executed. By not relying on background information in an image, the described system may be used in devices that are moved in use, such as a palm plot, personal digital assistant (PDA), a mobile telephone, a digital camera, and a mobile game machine.

Abstract: Provided is a system and method for object detection and tracking in a video stream. Frames of the video stream are divided into regions of interest and a probability that the region contains at least a portion of an object to be tracked is calculated for each region of interest. The regions of interest in each frame are then classified based on the calculated probabilities. A region of interest (RI) frame is then constructed for each video frame that reports the classification of regions of interest in the video frame. Two or more RI frames are then compared in order to determine a motion of the object. Also provided is a system executing the presently described method, as well as a device including the system. The device may be for example, a portable computer, a mobile telephone, or an entertainment device.