Smartphone-Based Methods and Systems
Arrangements involving portable devices (e.g., smartphones and tablet computers) are disclosed. One arrangement enables a content creator to select software with which that creator's content should be rendered—assuring continuity between artistic intention and delivery. Another utilizes a device camera to identify nearby subjects, and take actions based thereon. Others rely on near field chip (RFID) identification of objects, or on identification of audio streams (e.g., music, voice). Some technologies concern improvements to the user interfaces associated with such devices. Others involve use of these devices in connection with shopping, text entry, sign language interpretation, and vision-based discovery. Still other improvements are architectural in nature, e.g., relating to evidence-based state machines, and blackboard systems. Yet other technologies concern use of linked data in portable devices—some of which exploit GPU capabilities. Still other technologies concern computational photography. A great variety of other features and arrangements are also detailed.
1 - 7 . (canceled)
8 . A portable device including a processor, a memory, and plural sensors including at least a camera and a microphone, the aforesaid elements cooperating to define plural recognition agents, said agents being configured to read data from and write data to a blackboard data structure of the memory, the blackboard data structure also being configured to receive data from the sensors and compile queues of stored image data and audio data that said agents process.
9 . The portable device of claim 8 in which plural of the recognition agents are each configured to estimate a resource cost required to perform a function, and estimate a quality of result that may be achieved by such function, and to store such estimates in the blackboard structure, the device further including an event controller configured to assess such stored estimates from plural recognition agents and decide which recognition agent(s) to activate, based thereon.
10 . The portable device of claim 8 which further includes an event controller and an inference engine, the inference engine being configured to monitor the blackboard data structure and infer contextual data, the event controller being configured to use said contextual data in deciding which recognition agent(s) to activate.
11 . The portable device of claim 8 in which the device is configured to process audio and image streams in separate threads, and is configured so that each recognition agent runs in its own thread.
12 . The portable device of claim 25 wherein the sensors further include an accelerometer, and the device is configured to capture an image, determine a luminance value related thereto, assess acceleration associated with the image, assess saturation of the image and, based thereon, assess an image quality, and thereafter decide whether to invoke a watermark reading operation on the image based on the assessed image quality.
13 - 21 . (canceled)
22 . The portable device of claim 8 in which the recognition agents comprise at least one of an audio fingerprint recognition agent, a barcode recognition agent and an image watermark recognition agent.
23 . The portable device of claim 8 in which the recognition agents comprise at least two of an audio fingerprint recognition agent, a barcode recognition agent and an image watermark recognition agent.
24 . The portable device of claim 8 in which the recognition agents comprise an audio fingerprint recognition agent, a barcode recognition agent and an image watermark recognition agent.
25 . The portable device of claim 8 in which the recognition agents include an image watermark recognition agent.
26 . A method comprising:
storing image data captured by a camera portion of a portable device;
storing AGC data corresponding to the image data;
storing motion data corresponding to the portable device;
applying the image data to a classifier to yield classification data;
determining an image quality metric by reference to the stored AGC data, the stored motion data, and the classification data, said determining being performed by a processor comprises to perform such act; and
taking an action based on the determined image quality metric.
27 . The method of claim 26 in which the action comprises performing a watermark reading operation on the image data.
28 . The method of claim 26 that includes storing the image data, the AGC data, the motion data, the classification data, and the image quality metric, in a blackboard data structure.