IMAGE PROCESSING DEVICE, IMAGE PROCESSING METHOD, COMPUTER PROGRAM PRODUCT, AND IMAGE PROCESSING SYSTEM

• US 20160284098A1
• Filed: 03/21/2016
• Published: 09/29/2016
• Est. Priority Date: 03/23/2015
• Status: Active Grant

• Current Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Original Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: TAKATANI, Tsuyoshi, OKUMURA, Mayu, WATANABE, Tomoki, TASAKI, Tsuyoshi
• Granted Patent: US 10,075,652 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 7/292 Multi-camera tracking
• CPC Class Codes: G06T 7/41 based on statistical description of texture
• CPC Class Codes: H04N 23/90 Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums

Abstract

According to an embodiment, an image processing device includes an image acquirer, a tracker, an extractor, a feature amount acquirer, and an association controller. The image acquirer is configured to acquire a time series of images from each imaging device. The tracker is configured to track a position of an object in the time series of images. The extractor is configured to extract, from the time series of images, an observed value corresponding to a feature value in each of regions into which the time series of images is divided depending on a distance from the imaging device. The feature amount acquirer is configured to acquire a feature amount based on a deviation value of the observed value in a feature value distribution for the region. The association controller is configured to associate the tracked objects among multiple time series of images acquired from the imaging devices by using the feature amount.

Claims

1. An image processing device comprising:

an image acquirer configured to acquire a time series of images from each of a plurality of imaging devices;

a tracker configured to track a position of a target object in the time series of images;

a storage configured to store distributions of feature values for respective regions into which the time series of images is divided depending on a distance from a corresponding imaging device;

an extractor configured to extract an observed value corresponding to a feature value in each of the regions from the time series of images;

a feature amount acquirer configured to acquire a feature amount based on a deviation value of the observed value in the distribution for the corresponding region; and

an association controller configured to associate target objects tracked by the tracker with one another among multiple time series of images acquired from the plurality of imaging devices by using the feature amount.

2. The device according to claim 1, wherein the feature amount acquirer acquires, as the feature amount, a vector of the deviation value of each of observed values corresponding to a plurality of kinds of feature values.

3. The device according to claim 1, wherein the storage further stores the distribution of the feature value for each of the regions into which the time series of images is divided according to change in a moving direction of the target object in the time series of images.

4. The device according to claim 1, further comprising an updater configured to update the distribution stored in the storage according to the observed value.

5. The device according to claim 4, wherein

the storage stores initial distribution in advance, and

the updater shifts the initial distribution according to the observed value extracted in an initial state.

6. The device according to claim 1, wherein the feature value includes at least one of height, aspect ratio, moving speed, operation cycle, basic operation interval, and color information of the target object.

7. The device according to claim 1, wherein the plurality of imaging devices has imaging ranges different from one another.

8. An image processing method comprising:

acquiring a time series of images from each of a plurality of imaging devices;

tracking a position of a target object in the time series of images;

extracting, from the time series of images, an observed value corresponding to a feature value in each of regions into which the time series of images is divided depending on a distance from a corresponding imaging device;

acquiring a feature amount based on a deviation value of the observed value in a distribution for the corresponding region out of distributions of feature values for the respective regions; and

associating target objects tracked at the tracking with one another among multiple time series of images acquired from the plurality of imaging devices by using the feature amount.

9. A computer program product comprising a computer-readable medium containing a program executed by a computer, the program causing the computer to execute:

acquiring a time series of images from each of a plurality of imaging devices;

tracking a position of a target object in the time series of images;

extracting, from the time series of images, an observed value corresponding to a feature value in each of regions into which the time series of images is divided depending on a distance from a corresponding imaging device;

acquiring a feature amount based on a deviation value of the observed value in a distribution for the corresponding region out of distributions of feature values for the respective regions; and

associating target objects tracked at the tracking with one another among multiple time series of images acquired from the plurality of imaging devices by using the feature amount.

10. An image processing system comprising:

a plurality of imaging devices;

an image acquirer configured to acquire a time series of images from each of the plurality of imaging devices;

a tracker configured to track a position of a target object in the time series of images;

a storage configured to store distributions of feature values for respective regions into which the time series of images is divided depending on a distance from a corresponding imaging device;

an extractor configured to extract an observed value corresponding to a feature value in each of the regions from the time series of images;

a feature amount acquirer configured to acquire a feature amount based on a deviation value of the observed value in the distribution for the corresponding region;

an association controller configured to associate target objects tracked by the tracker with one another among multiple time series of images acquired from the plurality of imaging devices by using the feature amount; and

a presenter configured to present information indicating the target objects associated with one another among the multiple time series of images.