WO2017158622A3 - Method for managing image data at electronic device - Google Patents

Method for managing image data at electronic device Download PDF

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Publication number
WO2017158622A3
WO2017158622A3 PCT/IN2017/050092 IN2017050092W WO2017158622A3 WO 2017158622 A3 WO2017158622 A3 WO 2017158622A3 IN 2017050092 W IN2017050092 W IN 2017050092W WO 2017158622 A3 WO2017158622 A3 WO 2017158622A3
Authority
WO
WIPO (PCT)
Prior art keywords
electronic device
image data
managing image
rate
coding unit
Prior art date
Application number
PCT/IN2017/050092
Other languages
French (fr)
Other versions
WO2017158622A2 (en
Inventor
Anurag Mittal
Raj Gupta
Original Assignee
INDIAN INSTITUTE OF TECHNOLOGY MADRAS (IIT Madras)
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by INDIAN INSTITUTE OF TECHNOLOGY MADRAS (IIT Madras) filed Critical INDIAN INSTITUTE OF TECHNOLOGY MADRAS (IIT Madras)
Publication of WO2017158622A2 publication Critical patent/WO2017158622A2/en
Publication of WO2017158622A3 publication Critical patent/WO2017158622A3/en

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/503—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
    • H04N19/507—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction using conditional replenishment
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/132—Sampling, masking or truncation of coding units, e.g. adaptive resampling, frame skipping, frame interpolation or high-frequency transform coefficient masking
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/136—Incoming video signal characteristics or properties
    • H04N19/137—Motion inside a coding unit, e.g. average field, frame or block difference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/167—Position within a video image, e.g. region of interest [ROI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock

Abstract

Embodiments herein disclose a method for managing image data at an electronic device. The method includes receiving, by a coding unit, a plurality of image frame. Further, the method includes detecting, by the coding unit, a rate of motion of at least one object in each block of the image frames. Further, the method includes controlling, by the coding unit, a rate of transmission of each of the blocks of the image frames based on the rate of motion of the at least one object.
PCT/IN2017/050092 2016-03-16 2017-03-15 Method for managing image data at electronic device WO2017158622A2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
IN201641009144 2016-03-16
IN201641009144 2016-03-16

Publications (2)

Publication Number Publication Date
WO2017158622A2 WO2017158622A2 (en) 2017-09-21
WO2017158622A3 true WO2017158622A3 (en) 2018-08-09

Family

ID=59850788

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IN2017/050092 WO2017158622A2 (en) 2016-03-16 2017-03-15 Method for managing image data at electronic device

Country Status (1)

Country Link
WO (1) WO2017158622A2 (en)

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WO2018176000A1 (en) 2017-03-23 2018-09-27 DeepScale, Inc. Data synthesis for autonomous control systems
US10671349B2 (en) 2017-07-24 2020-06-02 Tesla, Inc. Accelerated mathematical engine
US11157441B2 (en) 2017-07-24 2021-10-26 Tesla, Inc. Computational array microprocessor system using non-consecutive data formatting
US11409692B2 (en) 2017-07-24 2022-08-09 Tesla, Inc. Vector computational unit
US11893393B2 (en) 2017-07-24 2024-02-06 Tesla, Inc. Computational array microprocessor system with hardware arbiter managing memory requests
US11561791B2 (en) 2018-02-01 2023-01-24 Tesla, Inc. Vector computational unit receiving data elements in parallel from a last row of a computational array
US11215999B2 (en) 2018-06-20 2022-01-04 Tesla, Inc. Data pipeline and deep learning system for autonomous driving
US11361457B2 (en) 2018-07-20 2022-06-14 Tesla, Inc. Annotation cross-labeling for autonomous control systems
US11636333B2 (en) 2018-07-26 2023-04-25 Tesla, Inc. Optimizing neural network structures for embedded systems
US11562231B2 (en) 2018-09-03 2023-01-24 Tesla, Inc. Neural networks for embedded devices
CN115512173A (en) 2018-10-11 2022-12-23 特斯拉公司 System and method for training machine models using augmented data
US11196678B2 (en) 2018-10-25 2021-12-07 Tesla, Inc. QOS manager for system on a chip communications
US11816585B2 (en) 2018-12-03 2023-11-14 Tesla, Inc. Machine learning models operating at different frequencies for autonomous vehicles
US11537811B2 (en) 2018-12-04 2022-12-27 Tesla, Inc. Enhanced object detection for autonomous vehicles based on field view
US11610117B2 (en) 2018-12-27 2023-03-21 Tesla, Inc. System and method for adapting a neural network model on a hardware platform
US10997461B2 (en) 2019-02-01 2021-05-04 Tesla, Inc. Generating ground truth for machine learning from time series elements
US11567514B2 (en) 2019-02-11 2023-01-31 Tesla, Inc. Autonomous and user controlled vehicle summon to a target
US10956755B2 (en) 2019-02-19 2021-03-23 Tesla, Inc. Estimating object properties using visual image data

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US6275617B1 (en) * 1993-07-12 2001-08-14 Sony Corporation Method and apparatus for separating/generating background and motion object planes
US6356664B1 (en) * 1999-02-24 2002-03-12 International Business Machines Corporation Selective reduction of video data using variable sampling rates based on importance within the image
US20120169923A1 (en) * 2010-12-30 2012-07-05 Pelco Inc. Video coding
US20150104062A1 (en) * 2013-10-14 2015-04-16 National Taipei University Of Technology Probabilistic neural network based moving object detection method and an apparatus using the same

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6275617B1 (en) * 1993-07-12 2001-08-14 Sony Corporation Method and apparatus for separating/generating background and motion object planes
US6356664B1 (en) * 1999-02-24 2002-03-12 International Business Machines Corporation Selective reduction of video data using variable sampling rates based on importance within the image
US20120169923A1 (en) * 2010-12-30 2012-07-05 Pelco Inc. Video coding
US20150104062A1 (en) * 2013-10-14 2015-04-16 National Taipei University Of Technology Probabilistic neural network based moving object detection method and an apparatus using the same

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
VARADARA.JAN ET AL.: "Background recovery from video sequences using motion parameters", IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING. ICASSP 2009, 26 May 2009 (2009-05-26), XP055533161, Retrieved from the Internet <URL:https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/0000989.pdf> *

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