applies f to a chunk of data corresponding to one frame from the Video object video, returning a list of results.


applies f to overlapping partitions corresponding to n video frames.


applies f to partitions with offset d.


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

Details and Options

  • VideoMapList can be used to detect temporal or spatial events in videos, such as object detection, motion detection or activity recognition.
  • VideoMapList returns a list of values corresponding to the results of f applied to an association including partial video data and their properties, such as video frames, audio data and time.
  • Using VideoMapList[f,video,n], the partition slides by one image frame.
  • 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 VideoMapList[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.
  • Frame variables n and d can be given as a scalar specifying the number of frames or a time Quantity object.
  • VideoMapList takes an Alignment option that specifies alignment of the time stamps with partitions.
  • VideoMapList supports video containers and codecs specified by $VideoDecoders.


open allclose all

Basic Examples  (2)

Compute the mean intensity of every frame:

Compute dominant colors per frame:

Create a weighted cloud of dominant colors:

Visualize dominant colors over time:

Scope  (4)

Function Specification  (2)

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

Check the keys of the provided association:

Process individual video frames:

Plot the result:

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

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

Plot the result:

Partition Specification  (2)

Process partitions corresponding to four frames:

Specify a partition size using a time Quantity:

By default, the offset of one frame is used:

Use an offset of four frames:

Specify an offset using a time Quantity:

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

Options  (1)

Alignment  (1)

By default, the values of the "Time" keys are aligned with the center of each partition:

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

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

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:

Applications  (1)

Find faces in a video:

Plot the number of faces detected over time:

Highlight detected faces in one of the frames:

Properties & Relations  (2)

VideoMapList can return lists of varying dimensions for each evaluation:

VideoMapTimeSeries cannot store such results:

VideoMapList does not return times corresponding to results:

Use VideoMapTimeSeries to get times back as well:

Wolfram Research (2020), VideoMapList, Wolfram Language function, (updated 2021).


Wolfram Research (2020), VideoMapList, Wolfram Language function, (updated 2021).


Wolfram Language. 2020. "VideoMapList." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2021.


Wolfram Language. (2020). VideoMapList. Wolfram Language & System Documentation Center. Retrieved from


@misc{reference.wolfram_2024_videomaplist, author="Wolfram Research", title="{VideoMapList}", year="2021", howpublished="\url{}", note=[Accessed: 20-May-2024 ]}


@online{reference.wolfram_2024_videomaplist, organization={Wolfram Research}, title={VideoMapList}, year={2021}, url={}, note=[Accessed: 20-May-2024 ]}