Obtaining information from an environment of a user of a wearable camera system

• US 10,178,291 B2
• Filed: 07/23/2015
• Issued: 01/08/2019
• Est. Priority Date: 07/23/2014
• Status: Active Grant

• Current Assignee: OrCam Technologies Ltd
• Original Assignee: OrCam Technologies Ltd
• Inventors: Wexler, Yonatan, Shashua, Amnon
• Primary Examiner(s): Moyer, Andrew M
• Application Number:
  US14/807,043
• Publication Number:
  US 20160026871A1
• Time in Patent Office: 1,265 Days
• Field of Search: 382103
• CPC Class Codes: G01S 3/7864 T.V. type tracking systems
• CPC Class Codes: G02B 2027/0138 comprising image capture systems, e.g. camera
• CPC Class Codes: G02B 2027/014 comprising information/image processing systems
• CPC Class Codes: G02B 2027/0178 Eyeglass type eyeglass details G02C
• CPC Class Codes: G02B 2027/0187 slaved to motion of at least a part of the body of the user, e.g. head, eye
• CPC Class Codes: G02B 27/0093 with means for monitoring data relating to the user, e.g. head-tracking, eye-tracking
• CPC Class Codes: G02B 27/017 Head mounted
• CPC Class Codes: G06F 1/163 Wearable computers, e.g. on a belt
• CPC Class Codes: G06F 1/1686 the I/O peripheral being an integrated camera
• CPC Class Codes: G06F 1/18 Packaging or power distribution
• CPC Class Codes: G06F 1/188 Mounting of power supply units
• CPC Class Codes: G06F 16/51 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/53 Querying
• CPC Class Codes: G06F 16/532 Query formulation, e.g. graphical querying
• CPC Class Codes: G06F 18/217 Validation; Performance evaluation; Active pattern learning techniques
• CPC Class Codes: G06F 2203/011 Emotion or mood input determined on the basis of sensed human body parameters such as pulse, heart rate or beat, temperature of skin, facial expressions, iris, voice pitch, brain activity patterns
• CPC Class Codes: G06F 3/005 Input arrangements through a video camera
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• CPC Class Codes: G06F 3/012 Head tracking input arrangements
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06F 3/0304 : Detection arrangements using opto-electronic means constructional details of pointing devices not related to the detection arrangement using opto-electronic means G06F3/033; optical digitisers G06F3/042
• CPC Class Codes: G06F 3/038 : Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry
• CPC Class Codes: G06Q 30/0246 : Traffic
• CPC Class Codes: G06Q 30/0257 : User requested
• CPC Class Codes: G06Q 30/0267 : Wireless devices
• CPC Class Codes: G06Q 30/0269 : based on user profile or attribute
• CPC Class Codes: G06T 2207/10004 : Still image; Photographic image
• CPC Class Codes: G06T 2207/10016 : Video; Image sequence
• CPC Class Codes: G06T 2207/30232 : Surveillance
• CPC Class Codes: G06T 7/20 : Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/74 : involving reference images or patches
• CPC Class Codes: G06T 7/97 : Determining parameters from multiple pictures depth or shape recovery from multiple images G06T7/55; stereo camera calibration G06T7/85
• CPC Class Codes: G06V 10/776 : Validation; Performance evaluation
• CPC Class Codes: G06V 20/20 : in augmented reality scenes
• CPC Class Codes: G06V 20/30 : in albums, collections or shared content, e.g. social network photos or video
• CPC Class Codes: G06V 20/41 : Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items segmenting video sequences G06V20/49
• CPC Class Codes: G06V 20/64 : Three-dimensional objects
• CPC Class Codes: G06V 20/647 : by matching two-dimensional images to three-dimensional objects
• CPC Class Codes: G06V 2201/07 : Target detection
• CPC Class Codes: G06V 2201/09 : Recognition of logos
• CPC Class Codes: G06V 40/16 : Human faces, e.g. facial parts, sketches or expressions
• CPC Class Codes: G06V 40/172 : Classification, e.g. identification
• CPC Class Codes: G06V 40/20 : Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: H04N 1/2112 : using still video cameras
• CPC Class Codes: H04N 23/45 : for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
• CPC Class Codes: H04N 23/50 : Constructional details
• CPC Class Codes: H04N 23/51 : Housings
• CPC Class Codes: H04N 23/57 : Mechanical or electrical details of cameras or camera modules specially adapted for being embedded in other devices
• CPC Class Codes: H04N 23/58 : Means for changing the camera field of view without moving the camera body, e.g. nutating or panning of optics or image sensors
• CPC Class Codes: H04N 23/61 : based on recognised objects
• CPC Class Codes: H04N 23/611 : where the recognised objects include parts of the human body
• CPC Class Codes: H04N 23/62 : Control of parameters via user interfaces
• CPC Class Codes: H04N 23/661 : Transmitting camera control signals through networks, e.g. control via the Internet
• CPC Class Codes: H04N 23/667 : Camera operation mode switching, e.g. between still and video, sport and normal or high- and low-resolution modes
• CPC Class Codes: H04N 23/6812 : based on additional sensors, e.g. acceleration sensors
• CPC Class Codes: H04N 23/73 : by influencing the exposure time
• CPC Class Codes: H04N 23/80 : Camera processing pipelines; Components thereof
• CPC Class Codes: H04N 5/44 : Receiver circuitry for the reception of television signals according to analogue transmission standards H04N5/14 takes precedence
• CPC Class Codes: H04N 7/183 : for receiving images from a single remote source
• CPC Class Codes: H04N 7/185 : from a mobile camera, e.g. for remote control

Abstract

A wearable apparatus and method are provided for executing actions based on triggers identified in an environment of a user. In one implementation, a wearable apparatus for storing information related to objects identified in an environment of a user is provided. The wearable apparatus includes a wearable image sensor configured to capture a plurality of images from the environment of the user and at least one processing device. The processing device may be programmed to process the plurality of images to detect an object entering a receptacle, process at least one of the plurality of images that includes the object to determine at least a type of the object, and based on the type of the object, generate information related to an action to be taken related to the object.

Claims

1. A wearable apparatus for storing information related to objects identified in an environment of a user, the wearable apparatus comprising:

a wearable image sensor configured to capture a plurality of images from the environment of the user while being worn by the user;

an attachment mechanism configured to enable the image sensor to be worn by the user; and

at least one processor programmed to;

receive image data representative of the plurality of images;

analyze, using at least one automated image processing technique, the image data representative of one or more of the plurality of images to detect one or more of a plurality of predetermined triggers;

detect, in the image data representative of at least one of the plurality of images, a trigger indicative of an object leaving a hand of the user;

responsive to detecting the trigger indicative of the object leaving the hand of the user, detect, in the image data representative of at least one of the plurality of images, the object entering a receptacle;

determine, based on the image data representative of at least one of the plurality of images that includes the receptacle, at least a type of the receptacle, the type of receptacle including at least one of a trash receptacle or a recycling receptacle;

detect, in a portion of the image data representative of at least one of the plurality of images that includes the object, one or more characteristics of the object;

determine, based on a comparison of the one or more characteristics in the portion of the image data with one or more images of representative objects stored in a database, at least a category for a type of the object;

determine, based on a comparison of the one or more characteristics in the portion of the image data with one or more images stored in the database and associated with at least one sub-category within the category, an identity of the object;

based on the identity of the object and on the type of the receptacle, generate information related to an action to be taken related to the object; and

provide an instruction to a controlled device associated with the user based on the generated information.

2. The wearable apparatus of claim 1, wherein the type of the object includes at least one or more of a type of product, a brand of product, and a product name.

3. The wearable apparatus of claim 1, wherein the information related to the action includes an indication to purchase a replacement of the object.

4. The wearable apparatus of claim 3, wherein the instruction causes an update to an action item list to include the object.

5. A method for storing information related to objects identified in an environment of a user of a wearable apparatus, comprising:

capturing a plurality of images from the environment of the user by a wearable image sensor while being worn by the user;

receiving, via at least one processing device, image data representative of the plurality of images;

analyzing, via the at least one processing device using at least one automated image processing technique, the image data representative of one or more of the plurality of images to detect one or more of a plurality of predetermined triggers;

detecting, in the image data representative of at least one of the plurality of images, a trigger indicative of an object leaving a hand of the user;

responsive to detecting the trigger indicative of the object leaving the hand of the user, detecting, via the at least one processing device, in the image data representative of at least one of the plurality of images, the object entering a receptacle;

determining, based on the image data representative of at least one of the plurality of images that includes the receptacle, at least a type of the receptacle, the type of receptacle including at least one of a trash receptacle or a recycling receptacle;

detecting, in a portion of the image data representative of at least one of the plurality of images that includes the object, one or more characteristics of the object;

determining, via the at least one processing device, at least a category for a type of the object based on a comparison of the one or more characteristics in the portion of the image data with one or more images of representative objects stored in a database;

determining, based on a comparison of the one or more characteristics in the portion of the image data with one or more images stored in the database and associated with at least one sub-category within the category, an identity of the object;

generating, based on the identity of the object and on the type of the receptacle, information related to an action to be taken related to the object; and

providing an instruction to a controlled device associated with the user based on the generated information.

6. The method of claim 5, wherein the type of the object includes at least one or more of a type of product, a brand of product, and a product name.

7. The method of claim 5, wherein the information related to the action includes an indication to purchase a replacement of the object.

8. The method of claim 7, wherein the instruction causes an update to an action item list to include the object.

9. A non-transitory computer readable medium storing instructions executable by at least one processing device, the instructions including instructions for:

capturing a plurality of images from the environment of a user by a wearable image sensor while being worn by the user;

receiving image data representative of the plurality of images;

analyzing, using at least one automated image processing technique, the image data representative of one or more of the plurality of images to detect one or more of a plurality of predetermined triggers;

detecting, in the image data representative of at least one of the plurality of images, a trigger indicative of an object leaving a hand of the user;

responsive to detecting the trigger indicative of the object leaving the hand of the user, detecting in the image data representative of at least one of the plurality of images, the object entering a receptacle;

determining, based on the image data representative of at least one of the plurality of images that includes the receptacle, at least a type of the receptacle, the type of receptacle including at least one of a trash receptacle or a recycling receptacle;

detecting, in a portion of the image data representative of at least one of the plurality of images that includes the object, one or more characteristics of the object;

determining at least a category fora type of the object based on a comparison of the one or more characteristics in the portion of the image data with one or more images of representative objects stored in a database;

determining, based on a comparison of the one or more characteristics in the portion of the image data with one or more images stored in the database and associated with at least one sub-category within the category, an identity of the object;

generating, based on the identity of the object and on the type of the receptacle, information related to an action to be taken related to the object; and

providing an instruction to a controlled device associated with the user based on the generated information.

10. The non-transitory computer readable medium of claim 9, wherein the type of the object includes at least one or more of a type of product, a brand of product, and a product name.

11. The non-transitory computer readable medium of claim 9, the information related to the action includes an indication to purchase a replacement of the object.

12. The non-transitory computer readable medium of claim 11, wherein the instruction causes an update to an action item list to include the object.