Pith. Sign in

RECORD

Shape-Adaptive Motion Estimation Algorithm for MPEG-4 Video Coding

PaperPDF from arXiv

data files

Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
X Bluesky LinkedIn Reddit Hacker News
F. Benboubker, F. Abdi, A. Ahaitouf

Multimedia · Submitted 5 Feb 2010

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The PSNR and computation time achieved by the proposed algorithm seem to be better than those obtained by most popular motion estimation techniques.

how it is stated · hedged possibility 0.88 read the record →

Comment (0) Read on arXiv ↗
Cite ▾
arXiv ID1002.1168 (version 1)
Pith IDTSFILF2K, Pith's permanent record of this paper and its review
CitationA. Ahaitouf, F. Abdi, F. Benboubker. "Shape-Adaptive Motion Estimation Algorithm for MPEG-4 Video Coding." arXiv:1002.1168 (2010). https://pith.science/paper/TSFILF2K
Claim paper

The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Open the compiled record

Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 2,304 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.06 · human participants 0.02 · controlled comparison 0.50 · randomized assignment 0.01 · states quantitative result 0.12 · compares with prior results 0.94 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

This paper presents a gradient based motion estimation algorithm based on shape-motion prediction, which takes advantage of the correlation between neighboring Binary Alpha Blocks (BABs), to match with the Mpeg-4 shape coding case and speed up the estimation process. The PSNR and computation time achieved by the proposed algorithm seem to be better than those obtained by most popular motion estimation techniques.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 This paper presents a gradient based motion estimation algorithm based on shape-motion prediction, which takes advantage of the correlation between neighboring Binary Alpha Blocks (BABs), to match with the Mpeg-4 shape coding case and speed up the estimation process. method 0.52 0.85 0.13 asserted 1.00
s1 The PSNR and computation time achieved by the proposed algorithm seem to be better than those obtained by most popular motion estimation techniques. result 0.97 0.91 0.72 hedged possibility 0.88

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 0.69.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

This paper presents a gradient based motion estimation algorithm based on shape-motion prediction, which takes advantage of the correlation between neighboring Binary Alpha Blocks (BABs), to match with the Mpeg-4 shape coding case and speed up the estimation process. The PSNR and computation time achieved by the proposed algorithm seem to be better than those obtained by most popular motion estimation techniques.

Human review

How Pith checks papers → · Full audit of this paper →

Discussion

Know something about this paper? Leave a comment, or highlight any passage above to comment on it.