Smartphone-based methods and systems

• US 9,218,530 B2
• Filed: 08/11/2011
• Issued: 12/22/2015
• Est. Priority Date: 11/04/2010
• Status: Active Grant

• Current Assignee: Digimarc Corporation
• Original Assignee: Digimarc Corporation
• Inventors: Davis, Bruce L., Rodriguez, Tony F.
• Primary Examiner(s): Saunders, Jr., Joseph
• Application Number:
  US13/207,841
• Publication Number:
  US 20120116559A1
• Time in Patent Office: 1,594 Days
• Field of Search: 700/94
• US Class Current: 1/1
• CPC Class Codes: G06F 3/002 Specific input/output arrangements not covered by G06F3/01 - G06F3/16 other optical apparatus G02B27/00
• CPC Class Codes: G06F 3/0236 using selection techniques to select from displayed items
• CPC Class Codes: G06F 3/0237 using prediction or retrieval techniques
• CPC Class Codes: G06F 3/04886 by partitioning the display area of the touch-screen or the surface of the digitising tablet into independently controllable areas, e.g. virtual keyboards or menus
• CPC Class Codes: G06V 20/20 in augmented reality scenes
• CPC Class Codes: G10H 2240/041 File watermark, i.e. embedding a hidden code in an electrophonic musical instrument file or stream for identification or authentification purposes audio watermarking G10L19/018
• CPC Class Codes: G10L 19/018 Audio watermarking, i.e. embedding inaudible data in the audio signal
• CPC Class Codes: H04M 1/72412 using two-way short-range wireless interfaces
• CPC Class Codes: H04M 2250/04 including near field communication means, e.g. RFID
• CPC Class Codes: H04M 2250/52 including functional features of a camera constructional features concerning the integration of cameras in portable phones H04M1/0264

Abstract

Methods and arrangements involving portable devices, such as smartphones and tablet computers, are disclosed. One arrangement enables a creator of content to select software with which that creator'"'"'s content should be rendered—assuring continuity between artistic intention and delivery. Another arrangement utilizes the camera of a smartphone 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 of the detailed 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.

Claims

1. A method comprising:

receiving, in a portable audio device, audio data representing samples of audio content, for rendering into human-perceptible sound;

applying a digital watermark decoding or audio fingerprinting algorithm to the received audio data to derive identification data therefrom;

by reference to the derived identification data, selecting a particular software program for use-with-said-audio-content rendering of said audio data into said human-perceptible sound, said selecting being performed by a processor in the portable audio device that is configured to perform such act; and

launching said selected software program;

wherein selection of the particular software program that renders the audio data is based on identification data derived from the audio data.

2. The method of claim 1 in which the selecting comprises selecting a particular rendering codec for the audio data, from among plural possible rendering codecs.

3. The method of claim 1 in which the selecting proceeds with reference to the derived identification data, and also with reference to context data, wherein a first software program is selected in a first context, and a second software program is selected in a second context.

4. The method of claim 3 in which the context data comprises age data.

5. The method of claim 3 in which the context data comprises gender data.

6. The method of claim 1 that includes downloading the selected software program to the portable audio device from a cloud repository after said selecting.

7. The method of claim 1 in which the portable audio device already includes a software program for rendering said audio data into human-perceptible sound, but said selecting identifies a different software program, wherein the method includes downloading said different software program and launching said different software program.

8. The method of claim 1 in which the selecting comprises identifying plural different software programs, and checking which of said identified software programs is available in storage of the portable audio device.

9. The method of claim 8 that includes finding that two or more of the identified software programs are available in storage of the portable audio device, and then automatically choosing between the available software programs based on an algorithm.

10. The method of claim 1 in which said selecting comprises selecting from among plural alternate, different software programs, each of which is technically suited for use in rendering the received audio content to a user.

11. The method of claim 1 in which said particular software was designated by a creator of the audio content.

12. The method of claim 1 that includes consulting a remote data structure to obtain an identification of said particular software program corresponding to the identification data derived from the received audio data.

13. A method comprising:

receiving, in a portable audio device, audio data representing samples of audio content, for rendering into human-perceptible sound;

applying a digital watermark decoding or audio fingerprinting algorithm to the received audio data to derive identification data therefrom;

by reference to the derived identification data, selecting a favored software program for rendering of said audio data into said human-perceptible sound, said selecting being performed by a processor in the portable device that is configured to perform such act; and

indicating the favored software program to a user;

wherein the favored software program for rendering the audio data is selected based on identification data derived from the audio data.

14. The method of claim 13 that includes:

receiving user input identifying a software program for rendering said audio data; and

if the software program identified by the received user input is not the favored software program, then limiting use of the identified software program with the audio content.

15. The method of claim 13 in which said favored software was designated by a creator of the audio content.

16. The method of claim 13 that includes consulting a remote data structure to obtain an identification of said favored software program corresponding to the identification data derived from the received audio data.

17. A method comprising:

receiving, in a portable audio device, audio data representing audio content, the audio content being of a type that can be rendered by first software in the portable audio device; and

in response to an attempt to render the audio content with the first software, the portable audio device indicating that second software should be used instead;

wherein a creator of the audio content designated the second software as preferred, for that creator'"'"'s audio.

18. The method of claim 17 that includes refusing to render the audio content with the first software.

19. The method of claim 17 that includes allowing only limited use of the audio content with the first software.

20. A method comprising the acts:

performing a digital watermark decoding or audio fingerprinting operation on received audio data to generate content identification data, said audio data representing samples of audio content for rendering into human-perceptible sound;

identifying a first context factor of a first context class, said first context class being selected from the list consisting of (a) computing context;

(b) user context;

(c) physical context;

(d) temporal context; and

(e) historical information about any of (a)-(d);

identifying a second context factor of a second context class, said second class being selected from said list and being different than the first context class;

selecting software for rendering said audio data, based on circumstances including (i) the content identification data;

(ii) the first context factor; and

(iii) the second context factor; and

rendering the received audio data to a user with said selected software;

wherein at least one of said acts is performed using a mobile computing apparatus that includes a microphone and a camera.

21. The method of claim 20 in which said identification operation comprises a fingerprinting operation.

22. The method of claim 20 in which said identification operation comprises a watermark decoding operation.

23. The method of claim 20 in which said selecting act is additionally based on a context factor in addition to said first and second context factors.

24. The method of claim 20 in which said selecting act proceeds with reference to a data structure in which software identification data is stored.

25. The method of claim 24 in which said data structure identifies plural different items of software—

any of which may be selected in the circumstances of said content identification data, the first context data, and the second context factor.

26. The method of claim 24 in which said data structure identifies plural different items of software—

all of which are to be selected in the circumstances of said content identification data, the first context data, and the second context factor.

27. The method of claim 24 in which at least certain software identified in said data structure was specified by a creator of the received content, for use with said received content.

28. The method of claim 20 in which said selecting act further involves an auction process.

29. The method of claim 20 in which the first factor is of the user context class, and the second factor is of the temporal context class.

30. The method of claim 20 in which the first factor is of the user context class, and the second factor is of the physical context class.

31. The method of claim 20 that includes receiving said content using said microphone.

32. the method of claim 20 in which said selected software was designated by a creator of the audio content.

33. The method of claim 20 that includes consulting a remote data structure to obtain an identification of said software corresponding to the identification data derived from the received audio data.