Author Topic: Latest Trends, Applications and Innovations in Motion Estimation Research  (Read 1670 times)

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Author : Mr. P. Vijaykumar, Aman Kumar, Sidharth Bhatia
International Journal of Scientific & Engineering Research Volume 2, Issue 6, June-2011
ISSN 2229-5518
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Abstractó Motion estimation is the process of determining motion vectors that describe the transformation from one 2D image to another, usually from adjacent frames in a video sequence. Motion estimation is a useful in estimating the motion of any object. Motion estimation has been conventionally used in the application of video encoding but nowadays researchers from various fields other than video encoding are turning towards motion estimation to solve various real life problems in their respective fields. This paper reviews some of the innovative uses of motion estimation algorithms in various applications such as in bionics, psychological studies, cinematography, medicine, security and space science.
Index Termsó breathing estimation, cinematography, gesture recognition, hand posture analysis, lunar lander, marker-less analysis, motion estimation, phase correlation, plant root growth, robotic heart surgery, three step search, variable shape search

1   INTRODUCTION                                                                      
THE field of motion estimation is undergoing substantial usage in non-conventional area nowadays, those which were not even thought about some years ago. These newfound uses of motion estimation are opening newer and wider options for researchers to apply these algorithms and get even better applications which are far more reliable and efficient than any of their predecessor techniques. These techniques are reaching farther and deeper into the avenues which are very new to the human knowledge. This paper goes in the direction of reviewing these newfound applications of motion estimation which are creating a revolution in the world of technology by creating more accurate and efficient solutions to long faced problems. The applications discussed in this paper are based on new motion estimation algorithms which reduce the complexity, resource requirement and response time of the systems they are used in. Some of these algorithms are fast block matching algorithms, optical flow estimation, phase correlation, etc. Using these algorithms researchers have developed new applications such as Traffic move-ment tracking, Studying plant root growth, Landing modules of rovers, Hand posture analysis, Human posture analysis, Gesture controlled gaming, Lip movement for user authentication, Cinematography, Robotic heart surgery, Breathing motion estimation.The paper consists of two sections. The first section briefly explains some of less computational complexity motion estimation algorithms. The second section deals with the applications of the motion estimation algorithms in the new fields and directions.
This section discusses some of the motion estimation algorithms which can either reduce the computational complexity or better the accuracy or both in a tradeoff. The algorithm can be selected according to the computational power available, time available for computing, the amount of accuracy required, the application being developed or any of the combinations of the above factors. Some of the algorithms that can be used to reduce the computational complexity in varying amounts according to the algorithm selected are: Fast Full Search Block Matching Algorithm [1], Three Step Search [2], New Three Step Search [3], Simple and Efficient Search [4], Four Step Search [5], Diamond Search [6], Adaptive Rood Pattern Search [7], New Fast and Efficient Two-Step Search Algorithm [8], Simplified Block Matching Algorithm for Fast Motion Estimation [9], Fast Block-Based True Motion Estimation Using Distance Dependent Thresholds [10], Sub-Pixel Motion Estimation Using Phase Correlation [11], Variable Shape Search [12], etc.. A few of these algorithms are discussed briefly in this section.
2.1 Three Step Search (TSS)
[2] This technique is a way to reduce the number of time search is done and to reach over a larger distance which saves computational power. This algorithm is used in the MPEG video standard. The first step is the same as in the basic block matching where search step is bigger than four pixels. At the next step the centre of current block is moved to the position of the best match from the previous step and matching is performed again but with smaller search step. Usually half the original size is used. This step can be repeated as many times as desired until one is satisfied with the result.

2.2 Variable Shape Search (Vss)
[12] The variable shape search mainly comprises three phases: (1) the big diamond search [6] to fit the directional centre-biased characteristics of the real-world video sequence. (2) The directional hexagon search to identify a small region where the best motion vector is expected to locate. (3) The small diamond search to select the best motion vector in the located small region. The VSS algorithm adopts two kinds of asymmetrical hexagonal search shapes in the step 2, with different directionality, separately, i.e., horizontal hexagon and vertical hexagon. The Mean Absolute Difference (MAD), rather than Mean Square Error (MSE), is used as the matching criterion to reduce the block-matching computation in practice.

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