Method and apparatus for accurate localization of points of interest

Patent metadata

Field	Value
Publication number	US-9390104-B2
Application number	US-201313954129-A
Country	US
Kind code	B2
Filing date	Jul 30, 2013
Priority date	Jul 30, 2013
Publication date	Jul 12, 2016
Grant date	Jul 12, 2016

Abstract

Geo-referenced and oriented media items may be used to determine a location of one or more points of interest depicted by the media items. A difference between an actual capture location and orientation and a reported location and orientation may be modeled according to one or more distributions, which distribution(s) may be used to assign one or more weights to each location in the world where such weight(s) may be considered to be a likelihood that a point of interest might have been seen by a capturing device. A density map may be acquired by superimposing the derived likelihoods, and a maximum, e.g., local maximum, may be determined to represent a location of a point of interest.

First claim

The invention claimed is:

1. A method comprising:
selecting, using at least one computing system, a plurality of digital media items, each media item of the plurality having associated capture information identifying a location and orientation of a digital media device capturing the media item;
generating, using the at least one computing system, a plurality of weights for each media item in the plurality, each weight of the media item's plurality of weights corresponding to a geographic location of a plurality of geographic locations, the weight reflects an estimated inaccuracy in the identified location and orientation of the digital media device and is generated using information including the media item's identified location and orientation, the generated weight for use in determining whether a point of interest depicted in the media item is located at the geographic location; and
for each geographic location of the plurality, aggregating, using the at least one computing system, the plurality of weights generated for the geographic location in connection with each media item of the plurality of media items, an aggregated weight for a given geographic location identifying a probability that at least one point of interest is located at the given geographic location.

2. The method of claim 1 , the generating further comprising:
generating each weight of the plurality of weights for a media item of the plurality of media items as a combined weight for a geographic location of the plurality of geographic locations, comprising, for each geographic location of the plurality of geographic locations:
generating, by the at least one computing system, a capture orientation inaccuracy weight for the media item using at least one statistical orientation inaccuracy model;
generating, by the at least one computing system, a capture location inaccuracy weight for the media item using at least one statistical location inaccuracy model; and
generating, by the at least one computing system, the combined weight for the media item by combining the capture orientation and location inaccuracies determined for the geographic location.

3. The method of claim 2 , wherein one of the capture orientation inaccuracy weight and the capture location inaccuracy weight is optional and the other is non-optional, and the combining resets the optional one of them so that the combined weight reflects only the non-optional one of the weights.

4. The method of claim 2 , the at least one statistical orientation inaccuracy model comprising at least one one-dimensional distribution centered on a mean orientation and having a standard deviation reflecting an orientation spread.

5. The method of claim 4 ,
for each geographic location u w of the plurality of geographic locations, the generating a capture orientation inaccuracy weight for the media item using at least one statistical orientation inaccuracy model further comprising the at least one computing system:
selecting a location along a line of sight indicated by the capture information's orientation, the line of sight location is selected so that a first distance between the geographic location u w and the capture location u p is the same as a second distance between the capture location u p and the line of sight location;
determining an orientation angle comprising an angle α(u w , u p ,θ p ) representing an orientation angle between the capture location's orientation and the geographic location's orientation, the mean orientation of the statistical orientation inaccuracy model is represented as θ p and the standard deviation is represented as σ θ ; and
determining the capture orientation inaccuracy weight for the media item and the geographic location u w using the angle α(u w , u p ,θ p ) and the standard deviation σ θ in accordance with the at least one statistical orientation inaccuracy model.

6. The method of claim 5 , the capture orientation inaccuracy weight for the media item and the geographic location u w is represented as G θ p (u w ;u p ,θ p ,σ θ ), which is determined using an expression:

G

θ
p

⁡

(

u
w

;

u
p

,

θ
p

,

σ
θ

)

=

1

2
⁢
π

⁢

σ
θ

⁢

ⅇ

-

α
⁡

(

u
w

,

u
p

,

θ
p

)

2

2
⁢

σ
θ
2

.

7. The method of claim 5 , wherein the capture orientation inaccuracy weight for the media item and the geographic location u w is determined using a statistical distribution for the at least one statistical orientation inaccuracy model.

8. The method of claim 2 , the at least one statistical location inaccuracy model comprising at least one two-dimensional model.

9. The method of claim 8 ,
for each geographic location u w of the plurality of geographic locations, the generating a capture location inaccuracy weight for the media item using at least one statistical location inaccuracy model further comprising the at least one computing system:
determining a distance represented as δ(u w ,u p ) between the capture location and the geographic location, the mean location of the statistical location inaccuracy model is the capture location represented as u p ; and
determining th

Assignees

• Yahoo Inc
• Excalibur Ip Llc

Inventors

• Thomee Bart

Classifications

• G06F16/444 Primary

  Spatial browsing, e.g. 2D maps, 3D or virtual spaces · CPC title

• G06F16/29 Primary

  Geographical information databases · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06F17/30241 Primary

  Physics · mapped topic

• G06F17/30256

  Physics · mapped topic