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Related Concept Videos

Downsampling01:20

Downsampling

806
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
806
Aliasing01:18

Aliasing

812
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
812
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
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Upsampling01:22

Upsampling

709
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
709
Reducing Line Loss01:18

Reducing Line Loss

447
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
447
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

1.5K
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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Compressed-Domain Video Retargeting.

Jiangyang Zhang, Shangwen Li, C-C Jay Kuo

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |August 14, 2015
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    Summary
    This summary is machine-generated.

    This study introduces a novel compressed-domain video retargeting method. It achieves high-quality video resizing on mobile devices with reduced memory and computational costs.

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    Area of Science:

    • Computer Vision
    • Digital Image Processing
    • Video Compression

    Background:

    • Traditional video retargeting methods operate in the spatial domain, requiring significant memory and computational resources.
    • These limitations make existing methods impractical for resource-constrained mobile devices.

    Purpose of the Study:

    • To develop a video retargeting solution that operates in the compressed domain.
    • To maintain high resizing quality while reducing memory and computational demands for mobile applications.

    Main Methods:

    • Exploiting low-level compressed domain features directly from the coded bit stream.
    • Utilizing motion vectors for motion information extraction.
    • Employing efficient column shape mesh deformation for simplified retargeting operations.

    Main Results:

    • The proposed compressed-domain solution achieves visual quality comparable or superior to state-of-the-art pixel-domain methods.
    • Demonstrates significantly lower computational and memory costs compared to existing approaches.

    Conclusions:

    • The developed compressed-domain video retargeting is scalable and practical for real-world applications, especially on mobile devices.
    • Offers an efficient alternative for content-aware video resizing without compromising quality.