IP Library Granted Patent US 12,408,632
Granted Patent B2
US 12,408,632 · App. 18/274,666 · Granted Sep 9, 2025

System and method for analyzing meting behavior of an animal species

Inventors: Marc Andre De Samber (Lommel, BE); Sri Andari Husen (Eindhoven, NL); Vladimir Ossin (Eindhoven, NL)
Assignee: SIGNIFY HOLDING B.V.
A01K29/005G06T7/20G06V40/10G06V40/20
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Quick Facts
Patent No.
US 12,408,632
App. No.
18/274,666
Filed
Jul 27, 2023
Granted
Sep 9, 2025
Kind
B2
Examiner
PHAM, QUANG
Art Unit
2685
USPC
340/573.3
Abstract

A system ( 100 ) for analyzing mating behavior of an animal species, comprising: an image-capturing device ( 110 ) configured to capture a plurality of time-successive image frames, and a processor ( 120 ), wherein the system is configured to detect and track at least one male ( 130 ) and female ( 140 ) of an animal species, register a motion pattern ( 150 ) of at least one of the tracked male and the tracked female, compare the registered motion pattern with a predetermined motion pattern ( 160 ), determine the likelihood of an action associated with a mating behavior between the tracked male and the tracked female, and, based on the determined likelihood, capture, via the image-capturing device, a set of time-successive image frames, wherein each image frame set of time-successive frame comprises at least one of the tracked male and the tracked female, and register the motion pattern as a function of the captured set of time-successive image frames.

Claims (81)

1. A system for analyzing a mating behavior of an animal species, comprising:

at least one image-capturing device configured to capture a plurality of time-successive image frames, and

a processor,

wherein the system is configured to, via the processor,

detect at least one male of the animal species based on at least one image frame of the plurality of time successive image frames, and

detect at least one female of an animal species based on at least one image frame of the plurality of time successive image frames,

wherein the system is further configured to:

track a male of the detected at least one male of the animal species based on the at least one image frame of the animal species, track a female of the detected at least one female of the animal species based on the at least one image frame of the animal species,

register at least one motion pattern of at least one of the tracked male and the tracked female,

compare the registered at least one motion pattern with at least one predetermined motion patterns,

determine the likelihood of at least one action associated with the mating behavior between the tracked male and the tracked female based on the compare of the registered at least one motion pattern with the at least one predetermined motion patterns, and

determine the likelihood of a mating between the tracked male and the tracked female based on the determined likelihood of the at least one action associated with the mating behavior between the tracked male and the tracked female.

2. The system of claim 1 , further configured to, based on the determined likelihood of the at least one action associated with the mating behavior between the tracked male and the tracked female,

capture, via the at least one image-capturing device, at least one set of time-successive image frames, wherein each image frame of the at least one set of time-successive frames comprises at least one of the tracked male and the tracked female, and

register the at least one motion pattern as a function of the captured at least one set of time-successive image frames,

whereby the system uses the registered at least one motion pattern iteratively in the comparison with the at least one predetermined motion patterns and the subsequent likelihood determination of at least one action associated with the mating behavior between the tracked male and the tracked female.

3. The system of claim 1 , further being configured to:

register a first motion pattern of the tracked male and the tracked female,

capture, via the at least one image-capturing device, a first set of time-successive image frames, wherein each image frame of the first set of time-successive frame comprises the tracked male and the tracked female, and

compare the registered first motion pattern with a predetermined first motion pattern of a male and a female of the animal species.

4. The system of claim 3 , further being configured to:

estimate a distance between the tracked male and the tracked female as a function of time, and

register the first motion pattern of the tracked male and the tracked female based on the estimated distance between the tracked male and the tracked female as the function of time.

5. The system of claim 3 , wherein the predetermined first motion pattern comprises a circulation by a male of the animal species around a female of the animal species.

6. The system of claim 1 , further being configured to:

register a second motion pattern of the tracked male, and

capture, via the at least one image-capturing device, a second set of time-successive image frames,

wherein each image frame of the second set of time-successive frame comprises the tracked male, and compare the registered second motion pattern with a predetermined second motion pattern of a male of the animal species.

7. The system of claim 1 , further being configured to:

register a third motion pattern of the tracked female, and

capture, via the at least one image-capturing device, a third set of time-successive image frames,

wherein each image frame of the third set of time-successive frame comprises the tracked female, and compare the registered third motion pattern with a predetermined third motion pattern of a female of the animal species.

8. The system of claim 1 , further being configured to:

determine a number of the detected at least one male of the animal species,

determine a number of the detected at least one female of the animal species,

determine a ratio between the number of the detected at least one female of the animal species and the number of the detected at least one male of the animal species, and

track the male of the detected at least one male of the animal species based on the ratio.

9. The system of claim 1 , further being configured to:

detect a plurality of females of the animal species within a predetermined radius of the detected at least one male, and track the male of the detected at least one male of the animal species based on the detected plurality of females of the animal species.

10. The system of claim 1 , wherein the animal species is chicken, whereby a male of the animal species is a rooster and a female of the animal species is a hen.

11. The system of claim 1 , further comprising:

at least one audio recording device,

wherein the system is further configured to:

via the at least one audio recording device, record at least one audio input from at least one of the tracked male and the tracked female, and

register the at least one motion pattern of at least one of the tracked male and the tracked female based on the at least one audio input.

12. A system for influencing mating behavior of an animal species, comprising:

at least one image-capturing device configured to capture a plurality of time-successive image frames,

a processor, and

wherein the system is configured to, via the processor,

detect at least one male of the animal species in space based on at least one image frame of the plurality of time successive image frames, and

detect at least one female of an animal species based on at least one image frame of the plurality of time successive image frames,

wherein the system is further configured to:

track a male of the detected at least one male of the animal species based on the at least one image frame of the animal species,

track a female of the detected at least one female of the animal species based on the at least one image frame of the animal species,

register at least one motion pattern of at least one of the tracked male and the tracked female,

compare the registered at least one motion pattern with at least one predetermined motion patterns,

determine the likelihood of at least one action associated with a mating behavior between the tracked male and the tracked female based on the comparison of the registered at least one motion pattern with the at least one predetermined motion patterns, and

determine the likelihood of a mating between the tracked male and the tracked female based on the determined likelihood of the at least one action associated with the mating behavior between the tracked male and the tracked female;

at least one light-emitting device arranged to emit light in the space, wherein the system is further configured to, based on at least one of the registered at least one motion pattern and the determined likelihood,

control at least one property of the at least one light-emitting device.

13. A method for analyzing a mating behavior of an animal species using a processor, comprising:

detecting at least one male of the animal species based on at least one image frame of a plurality of time successive image frames captured by the at least one image-capturing device,

detecting at least one female of an animal species based on at least one image frame of the plurality of time successive image frames,

tracking a male of the detected at least one male of the animal species based on the at least one image frame of the animal species,

tracking a female of the detected at least one female of the animal species based on the at least one image frame of the animal species,

registering at least one motion pattern of at least one of the tracked male and the tracked female,

comparing the registered at least one motion pattern with at least one predetermined motion patterns,

determining the likelihood of at least one action associated with the mating behavior between the tracked male and the tracked female based on the comparing of the registered at least one motion pattern with the at least one predetermined motion patterns, and and

determining the likelihood of a mating between the tracked male and the tracked female based on the determined likelihood of the at least one action associated with the mating behavior between the tracked male and the tracked female.

14. The method of claim 13 , further comprising, based on the determined likelihood of the at least one action associated with the mating behavior between the tracked male and the tracked female:

capturing at least one set of time-successive image frames, wherein each image frame of the at least one set of time-successive frame comprises at least one of the tracked male and the tracked female, and

registering the at least one motion pattern as a function of the captured at least one set of time-successive image frames, po 1 using the registered at least one motion pattern iteratively in the comparing with the at least one predetermined motion patterns and the subsequent likelihood determination of at least one action associated with the mating behavior between the tracked male and the tracked female.

15. A non-transitory computer readable medium comprising instructions executed by a computer for causing the computer to perform a method for analyzing a mating behavior of an animal species, comprises steps of:

detecting at least one male of the animal species based on at least one image frame of a plurality of time successive image frames captured by the at least one image-capturing device,

detecting at least one female of an animal species based on at least one image frame of the plurality of time successive image frames,

tracking a male of the detected at least one male of the animal species based on the at least one image frame of the animal species,

tracking a female of the detected at least one female of the animal species based on the at least one image frame of the animal species,

registering at least one motion pattern of at least one of the tracked male and the tracked female,

comparing the registered at least one motion pattern with at least one predetermined motion patterns,

determining the likelihood of at least one action associated with a mating behavior between the tracked male and the tracked female based on the comparing of the registered at least one motion pattern with the at least one predetermined motion patterns, and

determining the likelihood of a mating between the tracked male and the tracked female based on the determined likelihood of the at least one action associated with the mating behavior between the tracked male and the tracked female.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 27, 2023
From: DE SAMBER, MARC ANDRE; HUSEN, SRI ANDARI; OSSIN, VLADIMIR
To: SIGNIFY HOLDING B.V.
Reel/Frame 064409/0019 →
Priority Claims (1)
EP 21154765 · Feb 2, 2021 · regional
Continuity (1)
Related Publication 20240074412A1 · Mar 7, 2024
References Cited (54)
US 4503808A · McAlister · 1985 [cited by examiner]
US 5566679A · Herriott · 1996 [cited by examiner]
US 7428345B2 · Caspi · 2008 [cited by examiner]
US 7868769B2 · March · 2011 [cited by examiner]
US 7992521B2 · Bocquier · 2011 [cited by examiner]
US 8066179B2 · Lowe · 2011 [cited by examiner]
US 9538730B1 · Torres · 2017 [cited by examiner]
US 10080349B2 · Ikeda · 2018 [cited by examiner]
US 10089435B1 · Betts-Lacroix · 2018 [cited by examiner]
US 10575501B2 · Castro Lisboa · 2020 [cited by examiner]
US 20030165216A1 · Walker · 2003 [cited by examiner]
US 20080066693A1 · Bocquier · 2008 [cited by examiner]
US 20080178819A1 · Sia · 2008 [cited by examiner]
US 20110246223A1 · Rundensteiner · 2011 [cited by examiner]
US 20140015945A1 · Bench · 2014 [cited by examiner]
US 20150302241A1 · Eineren · 2015 [cited by examiner]
US 20150327518A1 · Han · 2015 [cited by examiner]
US 20160063310A1 · Okamoto · 2016 [cited by examiner]
US 20160078286A1 · Tani · 2016 [cited by examiner]
US 20170000081A1 · Betts-Lacroix · 2017 [cited by examiner]
US 20170000905A1 · Betts-Lacroix · 2017 [cited by examiner]
US 20170000906A1 · Betts-Lacroix · 2017 [cited by examiner]
US 20190037800A1 · Betts-Lacroix · 2019 [cited by examiner]
US 20190037801A1 · Betts-Lacroix · 2019 [cited by examiner]
US 20190037810A1 · Betts-Lacroix · 2019 [cited by examiner]
US 20190037811A1 · Betts-Lacroix · 2019 [cited by examiner]
US 20190042692A1 · Betts-Lacroix · 2019 [cited by examiner]
US 20190191665A1 · Schaevitz · 2019 [cited by examiner]
US 20200125849A1 · Labrecque · 2020 [cited by examiner]
US 20200219271A1 · Davis · 2020 [cited by examiner]
US 20200375148A1 · Magazzù · 2020 [cited by examiner]
US 20210227796A1 · Lopez Galarza · 2021 [cited by examiner]
US 20220125023A1 · Messinger · 2022 [cited by examiner]
US 20230094942A1 · Singh · 2023 [cited by examiner]
US 20240046493A1 · Murata · 2024 [cited by examiner]
US 20240188557A1 · Karounos · 2024 [cited by examiner]
CN 108717523A · 2018 [cited by applicant]
JP 2017143832A · 2017 [cited by applicant]
KR 1694946B1 · 2017 [cited by applicant]
KR 101694946B1 · 2017 [cited by applicant]
KR 1837026B1 · 2018 [cited by applicant]
WO 2007103886A2 · 2007 [cited by applicant]
WO 2010064892A1 · 2010 [cited by applicant]
Fazzari et al., Animal Behavior Analysis Methods Using Deep Learning_ A Survey (Year: 2024). [cited by examiner]
Fujibayashi et al., A Behavioral Analysis System MCFBM Enables Objective Inference of Songbirds Attention During Social Interactions (Year: 2024). [cited by examiner]
Lei et al., Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology (Year: 2021). [cited by examiner]
Lin et al., Video-based Bird Posture Recognition Using Dual Feature-rates Deep Fusion Convolutional Neural Network (Year: 2022). [cited by examiner]
Nasirahmadi et al., Implementation of Machine Vision for Detecting Behaviour of Cattle and Pigs (Year: 2017). [cited by examiner]
Tsai et al., A Motion and Image Analysis Method for Automatic Detection of Estrus and Mating Behavior in Cattle (Year: 2014). [cited by examiner]
Pereira et al., “Machine vision to identify broiler behavior”, Computers and Electronics in Agriculture 99 (2013) 194-199. [cited by applicant]
Shi et al., “Mating Behaviour and Fertility of Layer Breeders in Natural Mating Colony Cages: LED Light Environmental Effects”, Research Square 25 pgs. [cited by applicant]
Tsai et al., “A motion and image analysis method for automatic detection of estrus and mating behavior in cattle”, Computers and Electronics in Agriculture 104 (2014) 25-31. [cited by applicant]
Wurtz et al., “Recording behaviour of indoor-housed farm animals automatically using machine vision technology: Asystematic review”, Dec. 23, 2019. [cited by applicant]
Zaguri et al., “Targeted differential monochromatic lighting improves broiler breeder reproductive performance”, Physiology and Reproduction, 12 pgs. [cited by applicant]
Cited By (1)
US 12,660,797