Camera Motion Analysis in On-line MPEG Sequences

Tiburzi, F.; Bescós, Jesús

doi:10.1109/wiamis.2007.27

Cited by 12 publications

(12 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, when the camera moves fast, there will be significant displacement between consecutive frames, which may lead to an inaccurate estimation of the optical flow. Some approaches directly manipulate MPEG-compressed video to extract camera motion using the motion vectors as an alternative to optical flow [19,16,1,14,8,17,10]. Nonparametric motion models have also been proposed in the motion feature space [7].…”

Section: Related Workmentioning

confidence: 99%

Sensor-assisted camera motion analysis and motion estimation improvement for H.264/AVC video encoding

Wang

Seo

et al. 2012

Proceedings of the 22nd International Workshop on Network and Operating System Support for Digital Audio and Video

View full text Add to dashboard Cite

Camera motion information is one aspect that helps to infer higher-level semantic descriptions in many video applications, e.g., in video retrieval. However, an efficient methodology for annotating camera motion information is still an elusive goal. Here we propose and present a novel and efficient approach for the task of partitioning a video document into sub-shots and characterizing their camera motion. By leveraging location (GPS) and digital compass data, which are available from most current smartphone handsets, we exploit the geographical sensor information to detect transitions between two sub-shots based on the variations of both the camera location and the shooting direction. The advantage of our method lies in its considerable accuracy. Additionally, the computational efficiency of our scheme enables it to be deployed on mobile devices and to process videos while recording. We utilize this capability to show how the HEX motion estimation algorithm in the H.264/AVC encoder can be simplified with the aid of our camera motion information. Our experimental results show that we can reduce the computation of the HEX algorithm by up to 50% while achieving comparable video quality.

show abstract

Section: Related Workmentioning

confidence: 99%

Sensor-assisted camera motion analysis and motion estimation improvement for H.264/AVC video encoding

Wang

Seo

et al. 2012

Proceedings of the 22nd International Workshop on Network and Operating System Support for Digital Audio and Video

View full text Add to dashboard Cite

show abstract

“…Given the six-parameter affine transformation model for global motion estimation as worked on by many researchers in the past decades [4], [5], [7], [11], and [12], Tan et al [2] proposed a simplified approximated model under the circumstance that, during the transition across two neighboring frames, camera motion is primarily dominated by three parameters: camera pan, tilt, and zoom. …”

Section: Camera Motion Estimation In Mpeg Compressed Domainmentioning

confidence: 99%

“…Hesseler et al [6] utilized the texture information contained in the DCT coefficients and the motion vector field of MPEG-2 videos to detect the camera motion. Tiburzi et al [7] designed Manuscript Copyright (c) 2009 IEEE. Personal use of this material is permitted.…”

Section: Introductionmentioning

confidence: 99%

Fast Camera Motion Estimation in MPEG Compressed Domain

Weng

Jiang²

2009

IEEE Trans. Circuits Syst. Video Technol.

View full text Add to dashboard Cite

In this paper, we propose a new algorithm for fast estimation of camera motion directly in MPEG compressed domain, which starts from an existing and commonly used camera motion model to characterize the relationship between corresponding points of the neighboring frames, and then exploits the MPEG motion estimation and compensation techniques to derive closed-form estimation of all the three camera motion parameters, including pan, tilt, and zoom. The proposed algorithm features in extremely low computing cost and high processing speed with 50% improvement over the representative existing algorithms. Comparative experiments also reveal that the proposed algorithm achieves similar estimation precision for all the three camera motion parameters.

show abstract

“…Here we use a novel two-phase technique [40] which is motivated by the efficiency requirements of on-line operation. The first phase aims at detecting changes in the camera motion scheme represented by the motion field.…”

Section: Camera Motionmentioning

confidence: 99%