Y.Liu and T.S.Huang. Vehicle-type motion estimation from multi-frames images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(8):802--808, 1993.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....real traffic flows. Active projects in traffic surveillance have been funded in Europe [22] and the USA [10] These projects focus on specific problems such as handling occlusion, tracking objects while the camera itself is moving, and developing real time tracking systems (see [22] 11] 33] [51]) 2 Another application in which image sequence analysis has been used is the monitoring of human behavior in exhibition rooms (see [22] This system provides information on how much time people spend at the various exhibits, and the order the exhibits are visited. Similar systems have been ....

Y.Liu and T.S.Huang. Vehicle-type motion estimation from multi-frames images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(8):802--808, 1993.

....order to reduce the amount of produced information. In this paper we show the feasibility of our technique through a case study. The specific application domain we selected is highway monitoring [3] and more in particular the compression of video sequences generated by highway surveillance cameras[7] while the multimedia coding standard selected is the MPEG standard. The paper is organized as follows. Section 2 describes the methodology adopted; Section 3 describes the details of the customized MPEG coding algorithm; Section 4 reports the experimental results in terms of compression ratio ....

Y.Liu and T.S. Huang. "Vehicle Type Motion estimation from Multi-frame Images". "IEEE trans. on Pattern Analysis and machine Intelligence", 15(8), 1993.

....can take advantage of these rules in order to reduce the amount of produced information. The specific application domain we selected as a case study for this paper is highway monitoring [MB94] and more in particular the compression of video sequences generated by highway surveillance cameras[YH93]. The paper is organized as follows. Section 2 describes the methodology adopted; Section 3 describes the details of the customized MPEG coding algorithm; Section 4 gives some results as concluding remarks. 2 Methodology and Model The methodology adopted to design this algorithm is based on the ....

Y.Liu and T.S. Huang. "Vehicle Type Motion estimation from Multi-frame Images". "IEEE trans. on Pattern Analysis and machine Intelligence", 15(8),

....These works estimated the motion according to the camera center, that is, rotation around the axis through the camera center followed by translation. In the application of human computer interaction and navigation, it is more desirable to compute the motion according to the observer s center [15]. One of the major problems in motion recovery is the ambiguity problem. Multiple kinds of motion induce similar optical flow fields and it is difficult to determine the motion from the observed optical flow field. Horn [20] and Brodsky et al. 21] stated that the motion fields and their ....

Yuncai Liu and Thomas S. Huang, "Vehicle-type motion estimation from multi-frame images", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 8, pp. 802--808, 1993.

....frame, and (u i ; v i ) is its displacement vector. The ground truth for the vehicle motion is unknown. Also, since the rotation angle of the truck is too small (about 5 o ) it could not be estimated reliably using two view point correspondence and three view line correspondence algorithms [45]. Since we are testing the robustness of MMGLR and its ability to detect multiple models, and not the performance of the linear optic flow algorithm, we compare our results with those obtained when the linear optic flow algorithm is supplied with the correct data subset for each motion (see Table ....

Y. Liu and T. S. Huang, "Vehicle-type motion estimation from multi-frame images," IEEE Trans. Patt. Analysis Mach. Intell., vol. 15, no. 8, pp. 802--808, Aug. 1993. 28 LIST OF FIGURES

....= jj U jj 2 jj P jj 2 = jj Ujj2 X3 jj Y jj 2 is the depth scaled observer speed at Y at time t. We refer to as relative depth in this paper. 1. 2 Literature Survey In recent years there has been considerable interest in using long image sequences to recover motion and structure [1, 9, 13, 19, 21, 23, 15, 20, 24, 6, 5, 18, 7]. Most of the algorithms use monocular image sequences but a few use binocular image sequences [16, 25] A few of the algorithms are batch (processing all the data at once) 21, 6, 4, 20] but most use some type of recursive estimation method (for example, an extended Kalman filter) 4, 5, 10] or ....

....minimization or factorization methods [6, 20] Batch methods are conceptually less complicated but recursive estimation methods yield a best answer at any given time and may be computationally more feasible when using real time acquired data. Most methods are based on point correspondences [13, 10, 23, 15, 18], feature correspondences (for example corner points or straight line segments) 5, 25, 20, 6] or simple pixel correspondences [16] Only a few of the methods involve Kalman filtering of motion parameters that are derived from optical flow. In particular, the work proposed by De Micheli, Torre and ....

Y. Lui and T.S. Huang. Vehicle-type motion estimation from multi-frame images. IEEE PAMI, 15(8):802--808, 1993.

....Kalman filter to integrate the computed binocular motion parameters over time, thus providing a best estimate of the parameter values at each time. 2. LITERATURE SURVEY There is an extensive body of research on recovering monocular motion and structure parameters from long image sequences [6, 8, 23, 10, 29, 16, 25, 31, 5, 22, 7]. Typically these use pixel, point or feature based correspondence as the input and compute motion and structure parameters for monocular sequences. Due to depth speed ambiguity, 3D depth and 3D translational speed cannot be recovered, only their ratio. A few algorithms assume stereo image ....

Y. Lui and T.S. Huang. Vehicle-type motion estimation from multi-frame images. IEEE PAMI, 15(8):802-- 808, 1993.

....image plane they can robustly solve for u, then and finally, given the computed u and , they can solve for at each image point where there is an image velocity measurement. In recent years there has been considerable interest in using long image sequences to recover motion and structure [15, 18, 42, 28, 49, 25, 24, 58, 36, 48, 60, 14, 13, 41, 16]. Most of the algorithms use monocular image sequences but a few use image binocular sequences [37, 61] A few of the algorithms are batch (processing all the data at once) 49, 14, 10, 48] but most use some type of recursive estimation method (for example, an extended Kalman filter) 59, 10, 13, ....

....[14, 48, 42] Batch methods may be more accurate [48] but they are a form of post hoc analysis. Recursive estimation methods can yield a best answer at any given time and may be computationally more feasible when using real time acquired data. Most methods are based on point correspondences [28, 20, 58, 36, 41], feature correspondences (for example corner points or straight line segments) 13, 61, 48, 14] or simple pixel correspondences [37] Heel [25, 24] proposed a direct sequential method that computes 3 d motion parameters directly from spatio temporal intensity derivatives. Only a few of the ....

Y. Lui and T.S. Huang. Vehicle-type motion estimation from multi-frame images. IEEE PAMI, 15(8):802--808, 1993.

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Y. Lin and T. S. Huang. Vehicle-type motion estimation from multi-frame images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(8), August 1993.

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Y. Liu and T. S. Huang, "Vehicle-Type Motion Estimation from Multi-frame Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, pp. 802-808, 1993.

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