IMDSP-7.1

Phase-based Image Motion Estimation and Registration
Magnus Hemmendorff, Mats T Andersson, Hans Knutsson (Electrical Engineering, Linköping University)

Conventional gradient methods (optical flow), for motion estimation assume intensity conservation between frames. This assumption is often violated in real applications. The remedy is a novel method that computes constraints on the local motion. These constraint are given on the same form as in conventional methods. Thus, it can directly substitute the gradient method in most applications. Experiments indicate a superior accuracy, even on synthetic images where the intensity conservation assumption is valid. The conventional gradient methods seem obsolete.

IMDSP-7.2

Robust Estimation of Rigid Body 3-D Motion Parameters from Point Correspondences
Theophilos Papadimitriou (ETL, Dept. Applied Informatics, University of Macedonia), Kostantinos I Diamantaras (Dept. of Informatics, Technological Education Institute), Michael G Strintzis (Information Processing Lab, Dept. Electrical and Computer Eng.,Aristotle University of Thessaloniki), Manos Roumeliotis (Dept. of Applied Informatics, University of Macedonia)

The estimation of a rigid body 3-D motion parameters from perspective views is typically very sensitive to noise and also to the presence of outliers in the measurements. In this paper we present a robust 3-D motion estimation approach based on a previously proposed method using SVD analysis of the measurements matrix. On the introduction of noise and outliers the performance of the old method was seen to deteriorate rapidly. Here the problem is attacked by splitting the measurement set in smaller subsets and combining the properties of the resulting submatrices with the properties of the desired solution vector in order to obtain our estimate. The method is very robust and it has been succesfully tested in both artificial datasets and real images with up to 50% presence of outliers. In addition, the method is fast and more importantly, the estimate quality is independent of the percentage of outliers.

IMDSP-7.3

Rotational and Translational Motion Estimation and Selective Reconstruction in Digital Image Sequences
Mingqi Kong (Washington University in St. Louis.), Bijoy K Ghosh (Professor, Washington University in St. Louis)

This paper addresses the problem of motion estimation and selective reconstruction of objects undergoing rotational motion composed with translational motion. The goal is to derive the motion parameters belonging to the multiple moving objects, i.e. the angular velocities and the translational velocities and identify their locations at each time instance by selective reconstruction. These parameters and locations can be used for various purpose such as trajectory tracking, focus/shift attention of robot, etc. The innovative algorithm we have developed is based on angular velocity and translational velocity tuned 2D+T filters. One of the important facts about our algorithm is that it is effective for both spinning motion and orbiting motion, thus unifies the treatment of the two kinds of rotational motion. Also by tuning of the filters, we can derive the translational motion parameters and the rotational motion parameters separately, which has the advantage of making motion estimation faster and more robust comparing to estimating all of them simultaneously. The algorithm is simulated using synthesized image sequencies corrupted by noise and shows to be accurate and robust against noise and occlusion.

IMDSP-7.4

Fast structure from motion recovery applied to 3D image stabilization
Sridhar Srinivasan, Rama Chellappa (Center for Automation Research, University of Maryland)

In this paper, we address 3D image stabilization using a framework for the estimation of scene structure from a monocular motion field. We show that our algorithm rapidly and accurately determines the focus of expansion (FOE) in an optical flow field. This involves computing the least squares error of a large system of equations without actually solving the equations, to generate an error surface that describes the goodness of fit as a function of the hypothesized FOE. Consequently, we recover the rotational motion which we use to perform 3D image stabilization.

IMDSP-7.5

A Fast Motion Estimation Algorithm based on Multi-resolution Frame Structure
Byung Cheol Song, Jong Beom Ra (Department of Electrical Engineering, Korea Advanced Institute of Science and Technology)

We present a novel multi-resolution block matching algorithm (BMA) for fast motion estimation. At the coarsest level, a full search BMA (FSBMA) is performed for searching complex or random motion. Concurrently, spatial correlation of motion vector (MV) field is used for searching continuous motion. Here we present an efficient method for searching full resolution MVs without MV decimation even at the coarsest level. After the coarsest level search, two or three initial MV candidates are chosen for the next level. At the further levels, the MV candidates are refined within much smaller search areas. Simulation results show that in comparison with FSBMA, the proposed BMA achieves a speed-up factor over 710 with minor PSNR degradation of 0.2dB at most, under a normal MPEG2 coding environment. Furthermore, our scheme is also suitable for hardware implementation due to regular data-flow.

IMDSP-7.6

Hierarchical Locally Adaptive Multigrid Motion Estimation for Surveillance Applications
J. E. Santos Conde, A. Teuner, B. J. Hosticka (Fraunhofer Institute of Microelectronic Circuits and Systems, Finkenstr. 61, D-47057 Duisburg, Germany)

In this contribution we address the problem of detection and tracking of moving objects for surveillance or occupant detection systems. The primary goal in this framework is the motion estimation of the extracted foreground. To overcome the drawbacks characteristic of classical block matching techniques, this contribution presents a new feature based hierarchical locally adaptive multigrid (HLAM) block matching motion estimation technique based on a foreground detection procedure using an adaptive recursive temporal lowpass filter. It leads to a robust and precise motion field estimation, close to the true motion in the scene. The simulation results highlight the superior performance of the proposed method. It yields better performance than the classical exhaustive search (ES) and the modified three-step search (MTSS) technique in terms of the peak signal-to-noise ratio (PSNR).

IMDSP-7.7

Locally optimal, buffer-constrained motion estimation and mode selection for video sequences
Christian B Peel, Scott E Budge (Utah State University), Kyminh Liang, Chien-Min Huang (Sorenson Vision, Inc.)

We describe a method of using a Lagrange multiplier to make a locally optimal trade off between rate and distortion in the motion search for video sequences, while maintaining a constant bit rate channel. Simulation of this method shows that it gives up to 3.5 dB PSNR improvement in a high motion sequence. A locally rate-distortion (R-D) optimal mode selection mechanism is also described. This method also gives significant quality benefit over the nominal method. Though the benefit of these techniques is significant when used separately, when the optimal mode selection is combined with the R-D optimal motion search, it does not perform much better than the codec does with only the R-D optimal motion search.

IMDSP-7.8

Embedded Optical Flow Motion Compensation And Finite State Hierarchical Vector Quantization
Kunal Mukherjee, Amar Mukherjee (University of Central Florida)

We propose a video coding and delivery scheme which is geared towards low bit-rate and real-time performance requirements. We use a finite state wavelet-based hierarchical lookup vector quantization (FSWHVQ) scheme, which embeds the optical flow calculations in table- lookups. This video coding scheme is both fast (table- lookups) and accurate (dense motion field), and avoids the blocking artifacts and poor prediction which plagues block coding schemes at low bit rates. For restricted image compression/transmission scenarios like teleconferencing, for which a good training set may be available, the FSWHVQ scheme may be viewed as storing as an internal representation in its lookup tables, a valid and complete model of the problem domain.

IMDSP-7.9

Detection of Point Targets in Image Sequences by Hypothesis Testing: a Temporal Test First Approach
Alexis P Tzannes (Air Force Reasearch Lab), Dana H Brooks (CDSP Center, ECE Department, Northeastern University)

This paper addresses the problem of designing an efficient and effective image sequence processing scheme that will successfully detect very small (point) targets in a cluttered background when both the target and clutter are moving through the image scene. The specific application area was detection of targets such as airplanes in infrared (IR) image sequences of a cloudy sky which have been taken by a stationary camera. In general we assume that targets are typically one to two pixels in extent and move only a fraction of a pixel per frame, are often low amplitude, and are found in scenes which also contain evolving clutter, e.g. clouds. Our algorithm is based on signal processing and detection theory, includes a perfect measurement performance analysis, and can be made computationally efficient compared to other approaches. Thus the algorithm could be applicable to other image sequence processing scenarios, using other acquisition systems besides IR, such as detection of small moving objects or structures in a biomedical or biological imaging scenario or the detection of satellites, meteors or other celestial bodies in night sky imagery acquired using a telescope. We present a GLRT solution, perfect measurement analysis including ROC curves, and results using real-world infrared data.

IMDSP-7.10

Reliable Search Strategy for Block Motion Estimation by Measuring the Error Surface
Chan Yui Lam (Department of Electronic and Information Engineering,The Hong Kong Polytechnic University), Siu Wan Chi (Department of Electronic and Information Engineering, The Hong Kong Polytechnic University)

The conventional search algorithms for block matching motion estimation reduce the set of possible displacements for locating the motion vector. Nearly all of these algorithms rely on the assumption: the distortion function increases monotonically as the search location moves away from the global minimum. Obviously, this assumption essentially requires that the error surface be unimodal over the search window. Unfortunately, this is usually not true in real-world video signals. In this paper, we formulate a criterion to check the confidence of unimodal error surface over the search window. The proposed Confidence Measure of Error Surface, CMES, would be a good measure for identifying whether the searching should continue or not. It is found that this proposed measure is able to strengthen the conventional fast search algorithms for block matching motion estimation. Experimental results show that, as compared to the conventional approach, the new algorithm through the CMES is more robust, produces smaller motion compensation errors, and requires simple computational complexity.

IMDSP-7.11

Motion Estimation Using A Volume Conservation Hypothesis
Dominique Béréziat, Isabelle Herlin (INRIA), Laurent Younes (ENS Cachan)

Nowadays, motion estimation is one of the main subjects in computer vision. Many methods developed to compute motion make use of the optical flow hypothesis. These methods usually fail to capture motion of objects with intensity evolution. We propose a new approach to solve the motion computation problem with a different type of constancy hypothesis. Because we are mainly interested in deformable moving structures, we postulate that such a structure, within a temporal image sequence, is associated with a constant volume or a constant total intensity over time. We call this postulate it the volume conservation hypothesis. Results are displayed for clouds motion and deformation on meteorological satellites images.

IMDSP-7.12

Linear and Non-Linear Filters for Bock Based Motion Estimation
Virginie F Ruiz (Department of Cybernetics, The University of Reading)

Many techniques are currently used for motion estimation. In the block-based approaches the most common procedure applied is the block-matching based on various algorithms. To refine the motion estimates resulting from the full search or any coarse search algorithm, one can find few applications of Kalman filtering, mainly in the intraframe scheme. This paper presents an 8x8-block based motion estimation which uses the Kalman filtering technique to improve the motion estimates resulting from both the three step algorithm and the 16x16-block based Kalman application of [9]. In the interframe scheme, due to discontinuities in the dynamic behaviour of the motion vectors, we propose the filtering by approximated densities [10]. This application uses a simple form involving statistical characteristics of multi-modal distributions.

IMDSP-7.13

Optical Flow Estimation from Noisy Data Using Differential Techniques
Chun-Jen Tsai (Dept. of ECE, Northwestern University), Nikolas P Galatsanos (Dept. of EE, Illinois Institute of Technology), Aggelos K Katsaggelos (Dept. of ECE, Northwestern University)

Many optical flow estimation techniques are based on the differential optical flow equation. These algorithms involve solving over-determined systems of optical flow equations. Least squares (LS) estimation is usually used to solve these systems even though the underlying noise does not conform to the model implied by LS estimation. To ameliorate this problem, work has been done using the total least squares (TLS) method instead. However, the noise model presumed by TLS is again different from the noise present in the system of optical flow equations. A proper way to solve the system of optical flow equation is the constrained total least squares (CTLS) technique. The derivation and analysis of the CTLS technique for optical flow estimation is presented in this paper. It is shown that CTLS outperforms TLS and LS optical flow estimation.

IMDSP-7.14

Motion Field Estimation By Vector Rational Interpolation For Error Concealment Purposes
Sofia Tsekeridou (Aristotle University of Thessaloniki), Faouzi Alaya Cheikh, Moncef Gabbouj (Tampere University of Technology), Ioannis Pitas (Aristotle University of Thessaloniki)

A study on the use of vector rational interpolation for the estimation of erroneously received motion fields of an MPEG-2 coded video bitstream has been performed. Four different motion vector interpolation schemes have been examined using motion information from available top and bottom adjacent blocks since left or right neighbours are usually lost. The presented interpolation schemes are capable of adapting their behaviour according to neighbouring motion information. Simulation results prove the satisfactory performance of the novel nonlinear interpolation schemes and the success of their application to the concealment of predictively coded frames. The motion vector rational interpolation concealment method proves to be a fast method, thus adequate for real-time applications.

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Last Update: February 4, 1999 Ingo Höntsch