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David J. Kriegman, IEEE

Pages: pp. 2-3

As an undergraduate, I started subscribing to the IEEE Transactions on Pattern Analysis and Machine Intelligence ( TPAMI). At that time, I spent more money on pizza each week than on a student subscription. Everything was new to me then, and I was thrilled when each issue arrived. And by now, my bookshelf is a sea of bumble-bee yellow spines. Yet I still get excited whenever a new issue arrives in my mailbox. So, it is an honor to have been selected to be the next Editor-in-Chief (EIC) of TPAMI, and I hope that TPAMI's content will continue to motivate a new generation of students, as well as inform seasoned researchers and practitioners by providing the most important papers at a price that even students can afford.

Since its inception and as more specialized journals were spawned, TPAMI's content has evolved. Today, papers at the core of TPAMI are in computer vision and in pattern analysis and recognition. And in these areas, the last five years have been an extraordinary period of development and progress; I feel that we are at the cusp of a golden age. New theoretical insights supported by new hardware capabilities are fueling a wide variety of applications. Advances in raw computing power (speed and memory) have been complemented with the ubiquity of digital imaging; a look at the advertisements in the Sunday newspaper will reveal that the least expensive Web camera is now cheaper than the most expensive mouse. Digital photography has supplanted film photography, and low-cost cameras are embedded in a variety of mass-market devices (e.g., cell phones, PDAs, etc.). My colleagues tell me that within five years, the silicon cost of cameras will be less than a penny (packaging and a lens add a bit more to the cost). Approaches and algorithms that would have been implausible to implement a decade ago are now routine. Yet, it is the new scientific and engineering advances that are even more exciting to me. The field advances through a combination of deep thinking, hard experimentation, creative insights, and the infusion of new ideas from other disciplines. For example, today pattern recognition is largely an aspect of machine learning; TPAMI is pleased to have prominent members of the machine learning community on the Editorial Board.

There is unprecedented growth in our community and its output over the past five years. Consider the number of submissions to our conferences. In 2000, 466 papers were submitted to the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), while in 2004 nearly 1,000 papers were submitted. As I write this editorial, more than 500 papers have been submitted to TPAMI, and so the total number of submissions for 2004 is estimated to approach 700.

While most readers are aware that TPAMI is the preeminent journal for our field, they might be surprised to learn where it stands within a larger context. The most commonly used metric is the Institute for Scientific Information (ISI) impact factor, a measure of the average number of times each article is cited within two years after publication. According to the Journal Citation Report, TPAMI's impact factor of 3.82 for 2003 makes it the third highest ranked publication in electrical engineering and the ninth highest in computer science. It is the highest ranked IEEE Journal or Transactions. With a total of 11,380 citations in 2003, TPAMI is the most highly cited publication in computer science.

The success of TPAMI starts with the authors and the quality of the papers that they submit. Now, only one-third of the submissions are accepted, and it is the careful work of the reviewers who not only help to select the best papers, but provide critical feedback to help improve those papers that are accepted. There are few extrinsic rewards for reviewing, even though timely, thoughtful, and professional peer review is the basis for all decisions. And, the pool of reviewers is essentially you—the reader, the researcher, and the author. Each time you see an issue of TPAMI and note statistics like the impact factor, you should feel some pride in your contributions.

The review process for each manuscript is overseen by the members of the Editorial Board, the Associate Editors (AEs), who devote a tremendous amount of time and energy to the task and ultimately have to make very difficult decisions. Since a great deal of trust is placed in the AE's judgment, they are chosen based on the reputation of their research, their experience with review processes (e.g., paper reviewing, editorial boards, program committees, etc.), their integrity, and their commitment. We also strive for a diverse board who can broadly cover all topics within TPAMI's scope. A great deal of thanks are extended to the Editorial Board for your hard work and continued dedication.

As incoming EIC, I have to thank and acknowledge the former EICs with whom I've worked most closely. Ranghachar Kasturi first appointed me to TPAMI's editorial board, and under him I learned the ropes. Kevin Bowyer steered TPAMI during a challenging period, and through his dedication and integrity I learned how to deal with some of the sticky situations that occasionally arise. Rama Chellappa has been a source of continual support, and I have to thank him for the opportunity to serve as Associate Editor-in-Chief; he taught me how to pilot the ship, and it is with some trepidation that I take the helm.

One of the notable accomplishments over the past six years is a significant reduction in the submission to acceptance time (currently, averaging 8-9 months). Much of the credit is reserved for the IEEE Computer Society staff, namely, Elaine Stephenson, Hilda Hosillos (who no longer works on TPAMI), and Suzanne Werner. Under Suzanne's guidance, Hilda and Elaine have accelerated the review process—from author to reviewer to Editor-in-Chief, we have all received polite reminders prompting us to action. Julie Hicks tirelessly puts together each issue, while Alicia Stickley and Angela Burgess oversee everything, including helping to increase the number of pages that we can publish.

Yet as EIC, I will strive to further reduce the submission to publication period. This obsession arises because its reduction is in the best interests of readers and authors. At this point, the administrative aspects of handling papers are streamlined and efficient, and the greatest delay is in the review process. Without increasing anybody's workload, there are ways in which reviewers, editors, and even authors can help. Most delays from reviewers (and editors) arise because they become overcommitted (who can say "No"?), but fail to communicate that they cannot meet their commitments in a timely manner. It seems that every possible event has occurred: birth of a child, house burning down, family illness, changing universities, divorce, job promotion, etc. Authors can help too. Some submissions are really on (or outside of) the border of TPAMI's focus, and AEs often have trouble finding qualified reviewers in a reasonable time. If an author hasn't seen recent and related papers, he/she might consider another venue. But more often, papers that are poorly written and difficult to read languish because reviewers just aren't motivated to keep on reading. As an author, your paper is much more likely to be accepted and in a timely manner, if the reviewers enjoy reading your paper. And, you'll probably face fewer revisions!

The page budget of TPAMI has been increasing, though this increase is not as rapid as the increase in submissions. This forces us to strictly adhere to page limits for papers, and requires authors to succinctly express their contributions. Yet, we now have an opportunity to include supplemental material that is accessible via the Internet. Here, you can place descriptions of additional experiments, images, video, data, etc.

As noted earlier, our field is growing rapidly, and TPAMI will receive nearly 700 manuscripts this year, implying that about 2,000 reviews will be needed. Many qualified members of our research community are willing and able to help out, but may be overlooked. Editors can be myopic when looking for reviewers and ultimately may draw on too small a pool. If you'd like to volunteer, please don't hesitate to contact either the transactions ( or the Associate Editors in your research area.

Finally, I am pleased to announce that Professor David Fleet from the University of Toronto has been selected by the IEEE Computer Society Publications Board to serve as the Associate Editor-in-Chief of TPAMI for the next two years.His brief biography appears below. While David's research is well known, he also brings experience from the corporate world and sound judgment to the team. As AEIC, David will help to troubleshoot problem areas such as papers languishing in review, situations where I may have a conflict of interest, and other initiatives to improve the quality of TPAMI.

David J. Kriegman, Editor-in-Chief

About the Authors

Bio Graphic
David Fleet received the PhD degree in computer science from the University of Toronto in 1991. He is a professor of computer science at the University of Toronto. From 1991 to 2000, he was on faculty at Queen's University, Canada, in the Department of Computing and Information Science, with cross-appointments in psychology and electrical engineering. In 1999, he joined the Palo Alto Research Center (PARC), where he managed the Digital Video Analysis Group and the Perceptual Document Analysis Group. He returned to the University of Toronto in October 2003. In 1996, Dr. Fleet was awarded an Alfred P. Sloan Research Fellowship for his research on biological vision. His 1999 paper with Michael Black on probabilistic detection and tracking of motion boundaries received Honorable Mention for the Marr Prize at the IEEE International Conference on Computer Vision. His 2001 paper with Allan Jepson and Thomas El-Maraghi on robust appearance models for visual tracking was awarded runner-up for the best paper at the IEEE Conference on Computer Vision and Pattern Recognition. In 2003, his paper with Eric Saund, James Mahoney, and Dan Larner won the best paper award at ACM UIST '03. He has been associate editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence (2000-2004), and program cochair for the IEEE Conference on Computer Vision and Pattern Recognition in 2003. His research interests include computer vision, image processing, visual perception, and visual neuroscience. He has published research papers and one book on various topics including the estimation of optical flow and stereoscopic disparity, probabilistic methods in motion analysis, 3D people tracking, modeling appearance in image sequences, non-Fourier motion and stereo perception, and the neural basis of stereo vision.
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