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smallbug2000木虫 (著名写手)
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[求助]
哥的论文大修，哥很郁闷，哥不想改了
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投了一篇论文到计算机视觉相关的杂志，最近返回结果，三个审稿人，其中两个审稿人意见较少。另一个觉得算法的创新性不够，给了大修，悲剧的是这篇论文之前投到CVPR去，也是这个审稿人审的（CVPR据了我），因为审稿意见基本一样，故可以断定是同一审稿人。最终编辑给了大修，但是我很绝望，因为给大修的审稿人从一开始就不认可我的算法，我想既然我认真修改了，可能还是会被他据。将编辑及大修审稿人意见附后，在此向各位大牛咨询两件事：1）该论文是否值得大修，修后被据的概率多大？2）如果大修，如果对付审稿人这么尖锐的问题。在些感谢，对于好的建议发放金币。 Dear**, Reviewers have now commented on your paper. You will see that they are advising that you revise your manuscript. If you are prepared to undertake the work required, I would be pleased to reconsider my decision. The reviewers' comments can be found at the end of this email or can be accessed by following the provided link. Reviewers' comments: The paper was reviewed by three experts on the topic. The reviewers agree that the paper discusses an important problem worth pursuing. They, however, also unanimously point out short comings of the paper, most important of which is the lack of thorough theoretical and experimental validation of the claims as well as references to prior work. The paper needs major revision to be considered for publication. If the authors decide to submit a major revision, please make sure to address the points raised by the reviewers. Reviewer #2: : This paper deals with the problem of visual tracking with irregular object motion. The particle set shift approach based on analytic optimization is proposed to deal with the incorrect state dynamic model. Particles are first sampled by the state dynamic model and they are moved to higher likelihood regions by newton optimization by maximizing likelihoods. The efficacy of the proposed approach is demonstrated via experiments with real sequences. - Positive points: Practically effective approach - Negative points: Not novel approach, rather heuristic, not convincing experimental results : The main problem of this paper is the proposed approach is not novel. The proposed approach is quite similar to [18] except the fact that the proposed approach used newton optimization instead of mean shift. : The proposed approach is rather heuristic. In the algorithm, particle weights are only proportional to likelihood, and this holds true for SIR particle filter where particles are sampled from state dynamic model. However, since particles are moved to higher likelihoods artificially, the weights determined from likelihoods will no longer correctly represent the true posterior. The proposed approach is rather similar to the particle swarm optimization-based tracking, e.g., "" by X. ** et al in CVPR 2008. Another problem of the proposed approach is that it might result in worse tracking results when there are appearance changes caused by various issues such as pose and lighting changes. : Since the proposed work is based on particle filter, the optimal importance functions used for visual tracking are also relevant. If we can use the optimal importance function, the irregular motion can be handled at least partially. Thus the following papers should be cited and commented as related work: - : The supplementary video result is too limited. Only a result for a single short sequence is not sufficient to support the validity of the proposed approach. Why is there no rotational motion in the results? The paper says that the state is translation, scale, and rotation, but there is no rotational motion in the results in the paper and video. : There must be cases that all particles are outside the basin of convergence. Since the particle are shifted by local optimization, particles will diverge from the optimal positions and tracking will fail. In the proposed approach, there is no consideration of this possibility. : The optimization will increase the computational complexity considerably. It is necessary to compare the other algorithms under the same computational time, e.g., proposed framework with 100 particles and standard particle filter with 1000 particles. My current recommendation is major revision. If the authors want to make the paper accepted in spite of the limited novelty and contribution, I think the followings should be addressed in the revision: - Additional experiments with object appearance changes like illumination - Addition of a mechanism to deal with the local optima problems with additional experiments with related videos - Comparison under the same computational complexity for different tracking algorithms [ Last edited by smallbug2000 on 2012-9-6 at 09:52 ] |
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★ ★
感谢参与，应助指数 +1
smallbug2000: 金币+2, ★★★很有帮助 2012-09-06 17:27:12
感谢参与，应助指数 +1
smallbug2000: 金币+2, ★★★很有帮助 2012-09-06 17:27:12
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6楼2012-09-06 15:55:48
carsonwen
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2楼2012-09-06 10:30:45
【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
smallbug2000: 金币+2, ★★★很有帮助 2012-09-06 14:45:35
smallbug2000: 金币+2, ★★★很有帮助 2012-09-06 17:37:34
smallbug2000: 金币+2, ★★★很有帮助 2012-09-11 19:27:09
smallbug2000: 金币+4, ★★★★★最佳答案 2012-09-13 14:47:15
感谢参与，应助指数 +1
smallbug2000: 金币+2, ★★★很有帮助 2012-09-06 14:45:35
smallbug2000: 金币+2, ★★★很有帮助 2012-09-06 17:37:34
smallbug2000: 金币+2, ★★★很有帮助 2012-09-11 19:27:09
smallbug2000: 金币+4, ★★★★★最佳答案 2012-09-13 14:47:15
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这个修改意见不算多的，具体就是： 1、增加实验结果以验证你方法的有效性；（这个只要有数据，应该好办） 2、局部最优问题，这个较难回答，一种你找到方法；另外一种就是通过实验来说明； 3、与不同算法的比较。首先找找网上有没有现成的能出结果的代码吧；实在不行只有自己实现；话说实验室如果有做换个方向的话应该是有一定基础吧。 强烈建议：按照专家意见修改，不要回避，最终你会发现有收获的！！  |
3楼2012-09-06 12:27:52
wangzhipengj
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4楼2012-09-06 13:05:39
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