A new cross-diamond search algorithm for fast block motion estimation

Zhu, Shiping; Shen, Xiaodong

doi:10.1117/12.806714

Cited by 36 publications

(47 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Shan Zhu and Kai Kuang Ma proposed a simple, robust and efficient fast block-matching motion estimation algorithm, called diamond search (DS) [9]. The DS algorithm employs two search patterns, called large diamond search pattern (LDSP) and small diamond search pattern (SDSP).…”

Section: Motion Capturementioning

confidence: 99%

A vision-based navigation system of mobile tracking robot

Snášel

Abraham

2010

2010 IEEE International Conference on Systems, Man and Cybernetics

View full text Add to dashboard Cite

Abstract-Based on the study of developments in many fields of computer vision, a novel computer vision navigation system for mobile tracking robot is presented. According to the primary functions of this kind of robot, three irrelevant technologies, pattern recognition, binocular vision and motion estimation, make up of the basic technologies of our robot. The non-negative matrix factorization (NMF) algorithm is applied to detect the target. The application method of NMF in our robot is demonstrated. Interesting observations on distance measurement and motion capture are discussed in detail. The reasons resulting in error of distance measurement are analyzed. According to the models and formulas of distance measurement error, the error type could be found, which is helpful to decrease the distance error. Based on the diamond search (DS) technology applied in MPEG-4, an improved DS algorithm is developed to meet the special requirement of mobile tracking robot.

show abstract

Section: Motion Capturementioning

confidence: 99%

A vision-based navigation system of mobile tracking robot

Snášel

Abraham

2010

2010 IEEE International Conference on Systems, Man and Cybernetics

View full text Add to dashboard Cite

show abstract

“…7(a) shows the M2SE and SI values of some existing block matching methods, i.e., Full Search, Diamond Search [28], Hexagonal Search [29], and predictive motion vector field adaptive search technique (PMV-FAST) [30] (with early termination disabled). Note that the M2SE metric favors "true" VFs, e.g., PMVFAST outperforms a Full Search in M2SE value, whereas this is never the case for the MSE metric.…”

Section: A M2se Vs Simentioning

confidence: 99%

Smoothness Constraints in Recursive Search Motion Estimation for Picture Rate Conversion

Bartels

Haan

2010

IEEE Trans. Circuits Syst. Video Technol.

View full text Add to dashboard Cite

Abstract-Many motion compensation algorithms are based on block matching. The quality of the block correlation depends on the validity of the brightness constancy assumption and the assumption of fixed translational motion within a block. These assumptions are invalid in areas with texture changes, noise, lighting changes, and rapid deformations. Smoothness priors should enforce stable estimates in these regions by propagating neighboring estimates, while preserving hard object boundaries (piecewise smoothness). Most motion estimation algorithms that successfully implement these constraints are computationally complex. In this paper, we show an intuitive and computationally efficient way to implement them within the framework of (realtime) recursive search, targeting consumer-market embedded devices with limited resources.

show abstract

“…Since diamond search algorithm [9] is useful in finding the minimum residual in the neighborhood and is widely used in video coding, we use it in finding the minimum false alarm rate in the neighborhood of feature space. The proposed weak classifier mining is steered by partial derivatives in feature space.…”

Section: Introductionmentioning

confidence: 99%

Partial Derivative Guidance for Weak Classifier Mining in Pedestrian Detection

Liu

Wang

Liu

et al. 2011

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYBoosting over weak classifiers is widely used in pedestrian detection. As the number of weak classifiers is large, researchers always use a sampling method over weak classifiers before training. The sampling makes the boosting process harder to reach the fixed target. In this paper, we propose a partial derivative guidance for weak classifier mining method which can be used in conjunction with a boosting algorithm. Using weak classifier mining method makes the sampling less degraded in the performance. It has the same effect as testing more weak classifiers while using acceptable time. Experiments demonstrate that our algorithm can process quicker than [1] algorithm in both training and testing, without any performance decrease. The proposed algorithms is easily extending to any other boosting algorithms using a window-scanning style and HOG-like features.

show abstract

A new cross-diamond search algorithm for fast block motion estimation

Cited by 36 publications

References 0 publications

A vision-based navigation system of mobile tracking robot

A vision-based navigation system of mobile tracking robot

Smoothness Constraints in Recursive Search Motion Estimation for Picture Rate Conversion

Partial Derivative Guidance for Weak Classifier Mining in Pedestrian Detection

Contact Info

Product

Resources

About