Koninklijke Philips Corporation N.v.

Koninklijke Phillips Electronics N.v.

Koninlijke Phillip Electronics N. V.

Antonio Colmenarez

Srinivas Gutta

Miroslav Trajkovic

Damian M Lyons

Eric Cohen-Solal

Hugo Strubbe

Kaushal Kurapati

Peter J Janssen

Tomas Brodsky

Mi-Suen Lee

Vasanth Philomin

Michael D Pashley

A dynamic method and system for processing video source frames (e.g., a television movie) with a video processing system (VPS) that includes a processor, a memory structure, input devices, and an output display. The video source frames, which are received by the VPS from a video source, are executed by the processor. While the video source frames are being executed, a subset of the frames, called key frames, are extracted from the video source frames and stored in the memory structure. The extracting of the key frames is implemented in accordance with a frame extraction algorithm. The extracting is terminated prior to completion of execution of the video source frames. Following termination of extracting, the key frames are reviewed by a user with the output display to determine whether to watch the remainder of the video source frames. The key frames are erased after being reviewed.

Dynamic key frame generation and usage

An apparatus for detecting an emergency/law enforcement vehicle from a secondary vehicle. The apparatus includes: at least one camera mounted on the secondary vehicle; a display surface mounted inside an interior of the secondary vehicle for displaying video image data from the at least one camera; at least one of a pan, tilt, and zoom motor operatively connected to the at least one camera for providing an enhanced view of an emergency/law enforcement vehicle displayed on the display surface; and a controller for controlling the at least one pan, tilt, and zoom motors to provide the enhanced view. The apparatus alternatively also has the capability to detect, track and/or classify an emergency/law enforcement vehicle in the video image data.

Vehicle tracking and identification of emergency/law enforcement vehicles

An image processing system processes a sequence of images to generate a statistical model for each of a number of different persons to be tagged so as to be identifiable in subsequent images. The statistical model for a given tagged person incorporates at least one appearance feature, such as color, texture, etc., and at least one geometric feature, such as shape or position of a designated region of similar appearance within one or more images. The models are applied to subsequent images in order to perform a person detection, person location and/or person tracking operation. An action of the image processing system is controlled based on a result of the operation.

Person tagging in an image processing system utilizing a statistical model based on both appearance and geometric features

Using known methods of face recognition, appliances can be automatically initiated and/or adjusted as a user enters an environment, such as a home or a room. The environment is networked such that there is a communication link between a camera monitoring the entrance to the environment, a face recognition system, and the appliances. The method of automatically controlling a networked environment includes capturing a face image of an individual, storing the face image (i.e., in a memory), and associating at least one appliance setup to the face image. The method also includes comparing the face image to stored face images, retrieving the at least one appliance setup for a matched face image, and initiating the at least one appliance setup. An appliance setup controls turning on or off an appliance, such as an illumination source, a television, or a stereo.

Method and system for automatically controlling a personalized networked environment

An image processing system includes a combined display-camera having an array of interspersed display elements and camera elements, arranged substantially in a common plane of a flat panel or other display. Each of at least a subset of the camera elements has one or more imaging angles associated therewith, with the one or more imaging angles being selected to provide a desired imaging operation for the combined display-camera. The imaging angles of the camera elements can be selected to provide an imaging operation which approximates that of a lens-based single-camera system, a pin-hole camera system or other type of system. Each of the camera elements may include multiple image sensors, such that different imaging angles can be set for the different image sensors of a given camera element, and different perspectives of a scene can be generated in the image processing system.

Combined display-camera for an image processing system

A camera system comprising a camera, a monitor, an image detector, a touch screen, and a remote control. The monitor displays a field of view of a lens of the camera. The image detector provides a viewer image to the remote control whereby the remote control can determine a desired image within the field of view that the viewer is gazing upon. The touch screen enables a viewer of the monitor to point to the desired image of the field of view and provides signal(s) indicative of the pointing. The remote control is operable to activate various drives to pan and/or tilt the camera, or to zoom and/or focus the lens to the desired image and to follow any movement of the image within the field of view.

Remote camera control device

A system having a video display screen that provides video to a user. The position of the display screen is adjustable based upon the location of the user with respect to the display screen. The system includes at least one image capturing device trainable on a viewing region of the display screen and coupled to a control unit having image recognition software. The image recognition software identifies the user in an image generated by the image capturing device. The software of the control unit also generates at least one measurement of the position of the user based upon the detection of the user in the image.

Automatic positioning of display depending upon the viewer's location

A method and system for providing a mood based virtual photo album which provides photos based upon a sensed mood the viewer. The method may include the steps of capturing a first image of a facial expression of a viewer by a camera, providing the image to a pattern recognition module of a processor, determine a mood of the viewer by comparing the facial expression with a plurality of previously stored images of facial expressions having an associated emotional identifier that indicates a mood of each of the plurality of previously stored images, retrieving a set of photos from storage for transmission to the viewer based on the emotional identifier associated with the determined mood, and transmitting the set of photos in the form of an electronic photo album. A system includes a camera, a user interface for transmitting a first image of a facial expression of a viewer captured by the camera, a processor for receiving the transmitted image by the user interface, and including a pattern recognition module for comparing the image received by the processor with a plurality of images of facial expressions from a storage area to determine a mood of the viewer. A retrieval unit retrieves a set of electronic photos corresponding to the mood of the viewer, and transmits the set of electronic photos for display as a virtual photo album.

Mood based virtual photo album

Methods and apparatus are disclosed for predicting events using acoustic and visual cues. The present invention processes audio and video information to identify one or more (i) acoustic cues, such as intonation patterns, pitch and loudness, (ii) visual cues, such as gaze, facial pose, body postures, hand gestures and facial expressions, or (iii) a combination of the foregoing, that are typically associated with an event, such as behavior exhibited by a video conference participant before he or she speaks. In this manner, the present invention allows the video processing system to predict events, such as the identity of the next speaker. The predictive speaker identifier operates in a learning mode to learn the characteristic profile of each participant in terms of the concept that the participant 'will speak' or 'will not speak' under the presence or absence of one or more predefined visual or acoustic cues. The predictive speaker identifier operates in a predictive mode to compare the learned characteristics embodied in the characteristic profile to the audio and video information and thereby predict the next speaker.

Method and apparatus for predicting events in video conferencing and other applications

This invention provides an alarm system and method for adjusting the wake-up signals. The system includes a means for tracking the behavior of a person in a predetermined area under surveillance after the activation of an alarm clock, and a means for determining whether the person is motionless for a predetermined time period. Upon recognition that the observed behavior indicates the person is still sleeping, the wake-up signals are gradually increased. At the same time, the electrical power supplied to a plurality of electronic devices may be increased to assist the person to wake up.

Adaptive alarm system

A method and system for the automatic detection of a sleeping person and for adjusting electrical power supplied to a number of electronic devices; it includes a unit for observing the behavior of a person in a predetermined area under surveillance and a unit for analyzing output data from the observing unit to determine whether the observed behavior is associated with predefined sleeping behaviors. Upon recognition that the observed behavior indicates the sleeping state of a person, the electrical power supplied to the plurality of electronic devices is selectively adjusted according to predetermined criteria.

Automatic shut-off light system when user sleeps

A signal processing system processes a signal using a hidden Markov model (HMM) having a number of states determined at least in part based on application of an iterative algorithm to the model. The iterative algorithm adjusts the number of states of the model, based at least in part on closeness measures computed between the states, until the model satisfies a specified performance criterion. The model having the adjusted number of states is then utilized to determine a characteristic of the signal, and an action of the signal processing system is controlled based on the determined characteristic.

Method and apparatus for determining a number of states for a hidden Markov model in a signal processing system

A collaborative speed measurement device detection system provides early warning and increased reliability by sharing the responses of multiple detectors through a broadcast radio network. A vehicle with one detector (e.g., radar, laser detector) broadcasts a detection event to any other detectors in its vicinity. The receiving detectors generate a warning signal in response to the broadcast. The receivers can combine the results of multiple detections to generate a reliability estimate. The location of the detection events may be broadcast and used in generating alarms in the receiver as well.

Collaborative speed detection warning device

A security monitoring system including; an exit and entrance camera located at the exit and entrance of a structure; a detector for detecting the exit or entry of an individual; an image recording system for stroring images from the exit and entrance cameras; and a computer vision system for analyzing the stored images using a predetermined criteria to determine if the exiting and entering individuals are the same. In a preferred implementation, the system also includes a database for storing face image data for each authorized individual of the structure; and a face recognition system for comparing the stored images from the entry and entrance camera with the stored image data in the database and for determining if the exiting and entering individual is one of the authorized individuals.

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Peekskill, NY, United States of America

Antonio Colmenarez