Abstract: A method and system using a data-driven model for monocular face tracking are disclosed, which provide a versatile system for tracking three-dimensional (3D) images, e.g., a face, using a single camera. For one method, stereo data based on input image sequences is obtained. A 3D model is built using the obtained stereo data. A monocular image sequence is tracked using the built 3D model. Principal Component Analysis (PCA) can be applied to the stereo data to learn, e.g., possible facial deformations, and to build a data-driven 3D model (“3D face model”). The 3D face model can be used to approximate a generic shape (e.g., facial pose) as a linear combination of shape basis vectors based on the PCA analysis.

Abstract: A similarity search may be performed on the image of a person, using visual characteristics and information that is known about the person. The search identifies images of other persons that are similar in appearance to the person in the image.

Abstract: Images are analyzed by programmatic mechanisms for accessing one or more remote web pages to retrieve content on display at the remote web pages. The retrieved images may be analyzed to determine information about an object shown in a corresponding image of the content on display. At least a portion of the object shown in the corresponding image of the content on display may be made selectable and associated with the determined information. This determined information may subsequently be used, in for example, search applications.

Abstract: Embodiments described herein facilitate or enhance the implementation of image recognition processes which can perform recognition on images to identify objects and/or faces by class or by people.

Abstract: An index is provided that holds information about each image content item in a collection of items, For each image content item, a first information item identifying the image content item and its location on a network, and at least one of (i) a second information item identifying a signature value of an object in the image content, or (ii) identification of a recognized object in the image content.

Abstract: An embodiment provides for enabling retrieval of a collection of captured images that form at least a portion of a library of images. For each image in the collection, a captured image may be analyzed to recognize information from image data contained in the captured image, and an index may be generated, where the index data is based on the recognized information. Using the index, functionality such as search and retrieval is enabled. Various recognition techniques, including those that use the face, clothing, apparel, and combinations of characteristics may be utilized. Recognition may be performed on, among other things, persons and text carried on objects.

Abstract: An embodiment provides for enabling retrieval of a collection of captured images that form at least a portion of a library of images. For each image in the collection, a captured image may be analyzed to recognize information from image data contained in the captured image, and an index may be generated, where the index data is based on the recognized information. Using the index, functionality such as search and retrieval is enabled. Various recognition techniques, including those that use the face, clothing, apparel, and combinations of characteristics may be utilized. Recognition may be performed on, among other things, persons and text carried on objects.

Abstract: An embodiment provides for enabling retrieval of a collection of captured images that form at least a portion of a library of images. For each image in the collection, a captured image may be analyzed to recognize information from image data contained in the captured image, and an index may be generated, where the index data is based on the recognized information. Using the index, functionality such as search and retrieval is enabled. Various recognition techniques, including those that use the face, clothing, apparel, and combinations of characteristics may be utilized. Recognition may be performed on, among other things, persons and text carried on objects.

Abstract: A method and system corrects motion blur in time-of-flight (TOF) image data in which acquired consecutive images may evidence relative motion between the TOF system and the imaged object or scene. Motion is deemed global if associated with movement of the TOF sensor system, and motion is deemed local if associated with movement in the target or scene being imaged. Acquired images are subjected to global and then to local normalization, after which coarse motion detection is applied. Correction is made to any detected global motion, and then to any detected local motion. Corrective compensation results in distance measurements that are substantially free of error due to motion-blur.

Abstract: A method and system analyzes data acquired by image systems to more rapidly identify objects of interest in the data. In one embodiment, z-depth data are segmented such that neighboring image pixels having similar z-depths are given a common label. Blobs, or groups of pixels with a same label, may be defined to correspond to different objects. Blobs preferably are modeled as primitives to more rapidly identify objects in the acquired image. In some embodiments, a modified connected component analysis is carried out where image pixels are pre-grouped into regions of different depth values preferably using a depth value histogram. The histogram is divided into regions and image cluster centers are determined. A depth group value image containing blobs is obtained, with each pixel being assigned to one of the depth groups.

Abstract: A method and system dynamically calculates confidence levels associated with accuracy of Z depth information obtained by a phase-shift time-of-flight (TOF) system that acquires consecutive images during an image frame. Knowledge of photodetector response to maximum and minimum detectable signals in active brightness and total brightness conditions is known a priori and stored. During system operation brightness threshold filtering and comparing with the a priori data permits identifying those photodetectors whose current output signals are of questionable confidence. A confidence map is dynamically generated and used to advise a user of the system that low confidence data is currently being generated. Parameter(s) other than brightness may also or instead be used.

Abstract: Performance of pixel detectors in a TOF imaging system is dynamically adjusted to improve dynamic range to maximize the number of pixel detectors that output valid data. The invention traverses the system-acquired z depth, the brightness, and the active brightness images, and assigns each pixel a quantized value. Quantization values encompass pixels receiving too little light, normal light, to too much light. Pixels are grouped into quantized category groups, whose populations are represented by a histogram. If the number of pixels in the normal category exceeds a threshold, no immediate corrective action is taken. If the number of pixel receiving too little (or too much) light exceeds those receiving too much (or too little) light, the invention commands at least one system parameter change to increase (or decrease) light reaching the pixels. Controllable TOF system parameters can include exposure time, common mode resets, video gain, among others.

Abstract: Dynamic range of photodetector sensors useable in a TOF system is enhanced by capturing images of an object using multiple exposure time settings. Longer exposure settings more appropriately capture non-reflective and/or distant objects, while shorter exposure settings more appropriately capture reflective and/or closer objects. During parallel mode operation, detection signal readouts are taken from each photodetector at different time intervals within an overall exposure time. In sequential mode operation, detection signal readouts are taken and stored for each photodetector at the end of a first exposure time interval and the photodetectors are reset. After a second, different exposure time interval readouts are taken and stored, and the photodetectors reset, etc. In these modes one of the time exposure intervals will be relatively optimum for enhanced dynamic range operation.

Abstract: A method and system using a data-driven model for monocular face tracking are disclosed, which provide a versatile system for tracking three-dimensional (3D) images, e.g., a face, using a single camera. For one method, stereo data based on input image sequences is obtained. A 3D model is built using the obtained stereo data. A monocular image sequence is tracked using the built 3D model. Principal Component Analysis (PCA) can be applied to the stereo data to learn, e.g., possible facial deformations, and to build a data-driven 3D model (“3D face model”). The 3D face model can be used to approximate a generic shape (e.g., facial pose) as a linear combination of shape basis vectors based on the PCA analysis.