Depth-based adaptive search range algorithm for motion estimation in HEVC

Tsz Kwan Lee, Yui Lam Chan, Wan Chi Siu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)


High efficient video coding has been developed for ultra-high resolution and multi-view videos. It doubles the compression ratio compared to H.264/MPEG-4 AVC, but requires to adopt a very high computational quad-tree structure in motion estimation. Researchers mainly focus on fast mode decision on coding units or prediction units, and have reused the fast motion estimation techniques of H.264/MPEG-4 AVC. However, they do not fully utilize the characteristics of 3D video which is composed of texture streams and depth maps. The depth maps give cues to the objects in the same distance from the projected screen in a 3D scene. In addition to the high temporal correlation between frames, depth maps could be used to link up the objects in consecutive frames such that movements of the same object could be predicted. Therefore, the proposed algorithm aims to define an adaptive search range in motion estimation according to the predicted movements by depth intensity mapping in order to skip the unnecessary search points. Simulation results reveal that the proposed algorithm can reduce the complexity of motion estimation while the coding efficiency can be maintained.
Original languageEnglish
Title of host publication2014 19th International Conference on Digital Signal Processing, DSP 2014
Number of pages5
ISBN (Electronic)9781479946129
Publication statusPublished - 1 Jan 2014
Event2014 19th International Conference on Digital Signal Processing, DSP 2014 - Hong Kong, Hong Kong
Duration: 20 Aug 201423 Aug 2014


Conference2014 19th International Conference on Digital Signal Processing, DSP 2014
Country/TerritoryHong Kong
CityHong Kong


  • Adaptive search range
  • High efficiency video coding
  • Motion estimation
  • Texture and depth videos

ASJC Scopus subject areas

  • Signal Processing

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