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VideoMapTimeSeries
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VideoMapTimeSeries

[Experimental]

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applies f to each frame of the Video object video, returning a time series.

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VideoMapTimeSeries[f,video,n]

applies f to overlapping partitions of n video frames.

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VideoMapTimeSeries[f,video,n,d]

applies f to partitions with offset d.

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VideoMapTimeSeries[f,{video1,video2,…},…]

applies f to a list of inputs extracted from each videoi.

Details and Options

  • VideoMapTimeSeries can be used to detect temporal or spatial events in videos, such as object detection, motion detection or activity recognition.
  • VideoMapTimeSeries returns a TimeSeries whose values are the results of f applied to an association including partial video data and their properties, such as video frames, audio data and time.
  • The function f can access video and audio data using the following arguments:
  • #Imagevideo frames as Image objects
    #Audioa chunk of the audio as an Audio object
    #Timetime from the beginning of the video
    #TimeIntervalbeginning and end time stamps for the current partition
    #FrameIndexindex of the current output frame
    #InputFrameIndexindex of the current input frame
  • In VideoMapTimeSeries[f,{video1,video2,…},…], data provided to each of the arguments is a list where the i^(th) element corresponds to the data extracted from videoi.
  • Using VideoMapTimeSeries[f,video,n], the partition slides by one image frame.
  • Frame variables n and d can be given as a scalar specifying the number of frames or a time Quantity object.
  • VideoMapTimeSeries supports video containers and codecs specified by $VideoDecoders.
  • The following options can be given:
  • Alignment Centeralignment of the time stamps with partitions
    MetaInformationNoneinclude additional metainformation
    MissingDataMethodNonemethod to use for missing values
    ResamplingMethod"Interpolation"the method to use for resampling paths

Examples

open allclose all

Basic Examples  (2)Summary of the most common use cases

Compute the mean of the RGB colors for every video frame and plot them:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-2zudrb
In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-phe83r
Out[2]=2
In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-hhssci
Out[3]=3

Compute image distance between consecutive frames:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-7snv3j
In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-g59yzj
Out[2]=2

Plot the result, showing times with significant scene change:

In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-l9sk3u
Out[3]=3

Scope  (4)Survey of the scope of standard use cases

Function Specification  (2)

The function f receives an Association holding data for each partition:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-3ymldm

Check the keys of the provided association:

In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-45os7v

Process individual video frames:

In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-c5gqgl
Out[3]=3

Plot the result:

In[5]:=5
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https://wolfram.com/xid/0bc65iwk662vxgi-ctfzvy
Out[5]=5

The function f can operate on the audio data, provided as an Audio object:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-wdr3ow

Compute time-synchronous measurements on both image and audio data:

In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-tu2s9
Out[2]=2

Plot the result:

In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-4t5rke
Out[3]=3

Partition Specification  (2)

Process partitions corresponding to four frames:

In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-d6amem
In[7]:=7
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https://wolfram.com/xid/0bc65iwk662vxgi-7tak4e
Out[7]=7

Specify a partition size using a time Quantity:

In[10]:=10
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https://wolfram.com/xid/0bc65iwk662vxgi-z7tdhp
Out[10]=10

By default, the offset of one frame is used:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-k1bz6x
In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-ni5q8a
Out[2]=2

Use an offset of four frames:

In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-p18fnu
Out[3]=3

Specify an offset using a time Quantity:

In[4]:=4
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https://wolfram.com/xid/0bc65iwk662vxgi-1dwdb1
Out[4]=4

Specify an offset proportional to the partition size by a Scaled amount:

In[5]:=5
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https://wolfram.com/xid/0bc65iwk662vxgi-8n475z
Out[5]=5

Options  (1)Common values & functionality for each option

Alignment  (1)

By default, the time stamps are aligned with the center of each partition and correspond to the value of the "Time" key:

In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-rdmixs
In[20]:=20
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https://wolfram.com/xid/0bc65iwk662vxgi-uc7to8
Out[20]=20

Use AlignmentRight to return the computed property at the end of each partition:

In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-bwgfo
Out[3]=3

Use a custom alignment ranging from –1 (left) to 1 (right):

In[4]:=4
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https://wolfram.com/xid/0bc65iwk662vxgi-p3n29m
Out[4]=4

The boundaries of each partition are the start time for the first frame and the end time for the last frame of the partition. They can be queried using the "TimeInterval" key:

In[5]:=5
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https://wolfram.com/xid/0bc65iwk662vxgi-xco1xx
Out[5]=5

Applications  (2)Sample problems that can be solved with this function

Find portions of a video with constant images:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-c505kg

Define a function to detect whether an image has constant pixel values:

In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-c27aac

Apply the function to each frame and plot the result:

In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-n1c0a2
Out[3]=3

Count the number of cars in each frame:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-ycrg6k
Out[1]=1
In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-dmeek
Out[2]=2

Properties & Relations  (1)Properties of the function, and connections to other functions

VideoMapTimeSeries returns the results along with corresponding times in a TimeSeries:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-1c4n1a
In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-jiigek
Out[2]=2
In[3]:=3
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https://wolfram.com/xid/0bc65iwk662vxgi-693ukc
Out[3]=3

Use VideoMapList to get a list of results without time stamps:

In[4]:=4
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https://wolfram.com/xid/0bc65iwk662vxgi-9l448j
Out[4]=4

Possible Issues  (1)Common pitfalls and unexpected behavior

When the function returns a list, all lists should have similar dimensions:

In[1]:=1
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https://wolfram.com/xid/0bc65iwk662vxgi-3eea5d
In[2]:=2
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https://wolfram.com/xid/0bc65iwk662vxgi-ihho5y
Out[2]=2

Pad or trim the resulting lists to the same size to store them in the TimeSeries:

In[9]:=9
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https://wolfram.com/xid/0bc65iwk662vxgi-juqlqa
Out[9]=9
In[10]:=10
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https://wolfram.com/xid/0bc65iwk662vxgi-wcvkgb
Out[10]=10

Results may also be wrapped into other containers before being stored in a TimeSeries:

In[12]:=12
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https://wolfram.com/xid/0bc65iwk662vxgi-ps3fnv
In[13]:=13
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https://wolfram.com/xid/0bc65iwk662vxgi-5u64w7
Out[13]=13

Use VideoMapList to return the list of varying length lists:

In[14]:=14
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https://wolfram.com/xid/0bc65iwk662vxgi-vwcac3
Out[14]=14
Wolfram Research (2020), VideoMapTimeSeries, Wolfram Language function, https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html (updated 2021).
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Wolfram Research (2020), VideoMapTimeSeries, Wolfram Language function, https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html (updated 2021).

Text

Wolfram Research (2020), VideoMapTimeSeries, Wolfram Language function, https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html (updated 2021).

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Wolfram Research (2020), VideoMapTimeSeries, Wolfram Language function, https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html (updated 2021).

CMS

Wolfram Language. 2020. "VideoMapTimeSeries." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2021. https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html.

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Wolfram Language. 2020. "VideoMapTimeSeries." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2021. https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html.

APA

Wolfram Language. (2020). VideoMapTimeSeries. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html

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Wolfram Language. (2020). VideoMapTimeSeries. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html

BibTeX

@misc{reference.wolfram_2025_videomaptimeseries, author="Wolfram Research", title="{VideoMapTimeSeries}", year="2021", howpublished="\url{https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html}", note=[Accessed: 25-March-2025 ]}

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@misc{reference.wolfram_2025_videomaptimeseries, author="Wolfram Research", title="{VideoMapTimeSeries}", year="2021", howpublished="\url{https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html}", note=[Accessed: 25-March-2025 ]}

BibLaTeX

@online{reference.wolfram_2025_videomaptimeseries, organization={Wolfram Research}, title={VideoMapTimeSeries}, year={2021}, url={https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html}, note=[Accessed: 25-March-2025 ]}

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@online{reference.wolfram_2025_videomaptimeseries, organization={Wolfram Research}, title={VideoMapTimeSeries}, year={2021}, url={https://reference.wolfram.com/language/ref/VideoMapTimeSeries.html}, note=[Accessed: 25-March-2025 ]}