Abstract: The method of analyzing a video sequence for motion estimation comprises computing first matching energies for individual local displacements between frames of the video sequence using a first window around a pixel, and determining a minimum of the first matching energies. Second matching energies for motion configurations each including a plurality of local displacements between frames of the video sequence using the first window around said pixel are also computed. If none of the second matching energies satisfies a comparison criterion with the minimum of the first matching energies, a local displacement providing the minimum of the first matching energies is associated with said pixel.

Abstract: A method is proposed for analyzing an interlaced video signal including a first sequence of fields. A temporal regularity estimation process is applied to the first sequence of fields to compute a first metric. Inputs of the temporal regularity estimation process include pixel values from at least two fields having respective ranks differing by more than one in the sequence. The same temporal regularity estimation process is applied to second and third sequences of fields to compute second and third metrics. The second sequence is derived from the first sequence by swapping fields having ranks of the form 2k and 2k+1 for any integer k, while the third sequence is derived from the first sequence by swapping fields having ranks of the form 2k?1 and 2k. The first, second and third metrics are compared in a determination of the time arrangement of the fields in the first sequence.

Abstract: A direction of regularity, which minimizes a directional energy computed from pixel values of consecutive first and second frames of an input video sequence, is respectively associated with each pixel of the first frame and with each pixel of the second frame. Another direction of regularity (vz), which minimizes a directional energy computed from pixel values of the first and second frames, is also associated with an output pixel (z) of a frame of an output video sequence, located in time between the first and second frames. For processing such output pixel, the respective minimized directional energies for the output pixel, at least one pixel (z?) of the first frame and at least one pixel (z?) of the second frame are compared to control an interpolation performed to determine a value of the output pixel. The interpolation uses pixel values from at least one of the first and second frames of the input video sequence depending on the comparison of the minimized directional energies.

Abstract: In a method of analyzing an input video sequence, pixels of synthesized images of an output video sequence are associated with respective directions of regularity belonging to a predefined set of directions. A first subset of candidate directions is determined from the predefined set of directions for a region of a first image of the output sequence. For a corresponding region of a second synthesized image of the output sequence following the first image, a second subset of candidate directions is determined from the predefined set of directions, based on images of the input sequence and the first subset of candidate directions. The directions of regularity for pixels of this region of the second synthesized image are detected from the second subset of candidate directions. The recursive determination of the subsets of candidate directions provides a sparse geometry for efficiently analyzing the video sequence.

Abstract: In a method of analyzing an input video sequence, pixels of synthesized images of an output video sequence are associated with respective directions of regularity belonging to a predefined set of directions. A first subset of candidate directions is determined from the predefined set of directions for a region of a first image of the output sequence. For a corresponding region of a second synthesized image of the output sequence following the first image, a second subset of candidate directions is determined from the predefined set of directions, based on images of the input sequence and the first subset of candidate directions. The directions of regularity for pixels of this region of the second synthesized image are detected from the second subset of candidate directions. The recursive determination of the subsets of candidate directions provides a sparse geometry for efficiently analyzing the video sequence.

Abstract: Multiscale coefficients for each input video frame are distributed into K>1 groups. A first group of coefficients provides a representation of the frame at a first resolution level. For each integer k (1<k?K), a kth group of coefficients and the representation of the frame at the (k?i)th resolution level determine a representation of the frame at a kth resolution level. Directions of regularity (motion vectors) are associated with output pixels based on representations of successive input frames at one or more of the resolution levels. An interpolated pixel value is determined for the output pixel using each direction of regularity (motion vector) associated with this pixel by interpolating between pixel values from representations of successive input frames at one or more of the resolution levels.

Abstract: A method is proposed for analyzing an interlaced video signal including a first sequence of fields. A temporal regularity estimation process is applied to the first sequence of fields to compute a first metric. Inputs of the temporal regularity estimation process include pixel values from at least two fields having respective ranks differing by more than one in the sequence. The same temporal regularity estimation process is applied to second and third sequences of fields to compute second and third metrics. The second sequence is derived from the first sequence by swapping fields having ranks of the form 2k and 2k+1 for any integer k, while the third sequence is derived from the first sequence by swapping fields having ranks of the form 2k?1 and 2k. The first, second and third metrics are compared in a determination of the time arrangement of the fields in the first sequence.

Abstract: The method of analyzing a video sequence for motion estimation comprises computing first matching energies for individual local displacements between frames of the video sequence using a first window around a pixel, and determining a minimum of the first matching energies. Second matching energies for motion configurations each including a plurality of local displacements between frames of the video sequence using the first window around said pixel are also computed. If none of the second matching energies satisfies a comparison criterion with the minimum of the first matching energies, a local displacement providing the minimum of the first matching energies is associated with said pixel.

Abstract: A direction of regularity, which minimizes a directional energy computed from pixel values of consecutive first and second frames of an input video sequence, is respectively associated with each pixel of the first frame and with each pixel of the second frame. Another direction of regularity (vz), which minimizes a directional energy computed from pixel values of the first and second frames, is also associated with an output pixel (z) of a frame of an output video sequence, located in time between the first and second frames. For processing such output pixel, the respective minimized directional energies for the output pixel, at least one pixel (z?) of the first frame and at least one pixel (z?) of the second frame are compared to control an interpolation performed to determine a value of the output pixel. The interpolation uses pixel values from at least one of the first and second frames of the input video sequence depending on the comparison of the minimized directional energies.

Abstract: Multiscale coefficients for each input video frame are distributed into K>1 groups. A first group of coefficients provides a representation of the frame at a first resolution level. For each integer k (1<k?K), a kth group of coefficients and the representation of the frame at the (k?i)th resolution level determine a representation of the frame at a kth resolution level. Directions of regularity (motion vectors) are associated with output pixels based on representations of successive input frames at one or more of the resolution levels. An interpolated pixel value is determined for the output pixel using each direction of regularity (motion vector) associated with this pixel by interpolating between pixel values from representations of successive input frames at one or more of the resolution levels.

Abstract: In a method of analyzing an input video sequence, pixels of synthesized images of an output video sequence are associated with respective directions of regularity belonging to a predefined set of directions. A first subset of candidate directions is determined from the predefined set of directions for a region of a first image of the output sequence. For a corresponding region of a second synthesized image of the output sequence following the first image, a second subset of candidate directions is determined from the predefined set of directions, based on images of the input sequence and the first subset of candidate directions. The directions of regularity for pixels of this region of the second synthesized image are detected from the second subset of candidate directions. The recursive determination of the subsets of candidate directions provides a sparse geometry for efficiently analyzing the video sequence.