Comment Location:
https://www.blogger.com/comment.g?blogID=19209095&postID=1751249688937523606&isPopup=true
Summary:
UML is Unified Modeling Language and it is used to create flow charts of software design. There is already software for creating UML diagrams (they're a little "bulky" to use), but a combination of a sketch recognition and Powerpoint-esque system would be a welcome addition. This is exactly what Tahuti does. The users can draw the necessary boxes and lines and type in the necessary characters.
The users were required to perform 4 tasks and rank the difficulty in accomplishing them. The users performed the tasks on Rational Rose, a UML diagram creation software, and Tahuti. At the end of the study, the users were interviewed. Users expressed a higher satisfaction with Tahuti that with other UML diagram creation software and to a paint program. Some users complained Rational Rose was non-intuitive and it was difficult to perform the desired actions.
Discussion:
The author had a very good thing working in his favor. With the exception of letters, nearly every single shape in a UML diagram is composed of straight lines. This makes pre-processing of the sketch and identification of the sketch a much simpler matter than it would be otherwise. The only possible complaint I can see here is wondering if the user tasks were geared towards Tahuti's favor rather than a general set of tasks.
Thursday, December 2, 2010
Reading #29: Scratch Input Creating Large, Inexpensive, Unpowered and Mobile Finger Input Surfaces (Harrison)
Comment Location:
https://www.blogger.com/comment.g?blogID=19209095&postID=1742929146352552782&isPopup=true
Summary:
This paper attempts to recognize sketches by the sound created when the user creates the sketch. A stethoscope/microphone combination is placed on the drawing surface and the user creates the sketch. The amplitude of the sound wave is mapped out and analyzed to determine the shape drawn. For example, a rectangle typically has 4 amplitude peaks and a triangle typically has 3 amplitude peaks.
The author professed a high recognition rate of 90%, but he used some very simple shapes. The number of shapes used was very small as well. From what I read, the author assumed shapes were drawn in the same manner (very incorrect when sketching letters).
Discussion:
This paper introduced the idea of sound-based sketch recognition to me. However, sound-based recognition should be used to create a portable sketch recognition system. I want to see a "Magic Pen" that the user can use to sketch anywhere: on the bus, on the restroom wall, on the table or counter at Taco Bell. The sound and positioning data are collected to recognize the sketch on a separate screen.
By itself, sound recognition of sketches is not very effective. There are simply too many variations for a single shape and too few features to identify the shapes. In addition, many of the variations of shapes overlap with each other, making distinction between shapes very difficult. I am not the only one to say this. There is at least one other paper on this topic that expresses similar sentiments.
https://www.blogger.com/comment.g?blogID=19209095&postID=1742929146352552782&isPopup=true
Summary:
This paper attempts to recognize sketches by the sound created when the user creates the sketch. A stethoscope/microphone combination is placed on the drawing surface and the user creates the sketch. The amplitude of the sound wave is mapped out and analyzed to determine the shape drawn. For example, a rectangle typically has 4 amplitude peaks and a triangle typically has 3 amplitude peaks.
The author professed a high recognition rate of 90%, but he used some very simple shapes. The number of shapes used was very small as well. From what I read, the author assumed shapes were drawn in the same manner (very incorrect when sketching letters).
Discussion:
This paper introduced the idea of sound-based sketch recognition to me. However, sound-based recognition should be used to create a portable sketch recognition system. I want to see a "Magic Pen" that the user can use to sketch anywhere: on the bus, on the restroom wall, on the table or counter at Taco Bell. The sound and positioning data are collected to recognize the sketch on a separate screen.
By itself, sound recognition of sketches is not very effective. There are simply too many variations for a single shape and too few features to identify the shapes. In addition, many of the variations of shapes overlap with each other, making distinction between shapes very difficult. I am not the only one to say this. There is at least one other paper on this topic that expresses similar sentiments.
Reading #28: iCanDraw? – Using Sketch Recognition and Corrective Feedback to Assist a User in Drawing Human Faces (Dixon)
Comment Location:
http://pacocomputer.blogspot.com/2010/11/reading-28-icandraw-using-sketch.html
Summary:
This paper presents the idea of helping a user draw a sketch correctly. It also presents a general method for guiding a user's sketch and nine ideas for assistive sketch recognition in general. Most users are not skilled at drawing on a computer, or drawing at all. iCanDraw allows users to create accurate sketches. The user's sketches were more accurate with the assistance of the iCanDraw system.
Before the user starts sketching, the iCanDraw system analyzes the face image and extracts relevant data from it to use for the guidance interface. The user can verify the accuracy of his or her sketch with the "Check my work" option. It checks the accuracy of the user's lines with the "correct", computer-generated version.
Discussion:
If I remember correctly, Prof. Hammond presented this paper's contents in class. I like the idea of getting the face correct, but it doesn't really allow for artistic creativity. The system pretty much tells you what to draw, so why doesn't it just draw the face for you and save you the trouble? One more thing: does this system work for someone who ISN'T bald?
http://pacocomputer.blogspot.com/2010/11/reading-28-icandraw-using-sketch.html
Summary:
This paper presents the idea of helping a user draw a sketch correctly. It also presents a general method for guiding a user's sketch and nine ideas for assistive sketch recognition in general. Most users are not skilled at drawing on a computer, or drawing at all. iCanDraw allows users to create accurate sketches. The user's sketches were more accurate with the assistance of the iCanDraw system.
Before the user starts sketching, the iCanDraw system analyzes the face image and extracts relevant data from it to use for the guidance interface. The user can verify the accuracy of his or her sketch with the "Check my work" option. It checks the accuracy of the user's lines with the "correct", computer-generated version.
Discussion:
If I remember correctly, Prof. Hammond presented this paper's contents in class. I like the idea of getting the face correct, but it doesn't really allow for artistic creativity. The system pretty much tells you what to draw, so why doesn't it just draw the face for you and save you the trouble? One more thing: does this system work for someone who ISN'T bald?
Reading #27: K-Sketch: A 'Kinetic' Sketch Pad for Novice Animators (Davis)
Comment Location:
https://www.blogger.com/comment.g?blogID=19209095&postID=3549141404676567109&isPopup=true
Summary:
Here's a fun idea for anyone who's tried using Maya or any other 2D model software for animation. This paper introduces K-Sketch to make the creation of animated models very simple and intuitive. The author conducted several interviews to ensure the design of the system was acceptable.
The author determined the uses the K-Sketch system would be employed for and strove to ensure those purposes could be accomplished. For example, professional animators may use K-Sketch to do a presentation and amateurs may use K-Sketch to doodle or create an animation for entertainment purposes.
User testing was conducted by comparing K-Sketch against Powerpoint's animation capabilities. Users typically needed less help to accomplish tasks in K-Sketch and they accomplished those tasks in less time with K-Sketch than Powerpoint. The user satisfaction was generally greater towards K-Sketch than Powerpoint.
Discussion:
Here's what I want to see: an evolved form of K-Sketch that allows the user to save the models in file formats accepted by game programming systems (like XNA). Even better, I would like to scan in a few sketches of a person and use those as the basis for an animated model. This would close the gap between handrawn pictures and animated models. I also want to do this in 3D.
It's a good thing the author did the interviews prior to development. It's a great way to make sure you do the job right and sadly, not a lot of papers (that present systems) do that.
https://www.blogger.com/comment.g?blogID=19209095&postID=3549141404676567109&isPopup=true
Summary:
Here's a fun idea for anyone who's tried using Maya or any other 2D model software for animation. This paper introduces K-Sketch to make the creation of animated models very simple and intuitive. The author conducted several interviews to ensure the design of the system was acceptable.
The author determined the uses the K-Sketch system would be employed for and strove to ensure those purposes could be accomplished. For example, professional animators may use K-Sketch to do a presentation and amateurs may use K-Sketch to doodle or create an animation for entertainment purposes.
User testing was conducted by comparing K-Sketch against Powerpoint's animation capabilities. Users typically needed less help to accomplish tasks in K-Sketch and they accomplished those tasks in less time with K-Sketch than Powerpoint. The user satisfaction was generally greater towards K-Sketch than Powerpoint.
Discussion:
Here's what I want to see: an evolved form of K-Sketch that allows the user to save the models in file formats accepted by game programming systems (like XNA). Even better, I would like to scan in a few sketches of a person and use those as the basis for an animated model. This would close the gap between handrawn pictures and animated models. I also want to do this in 3D.
It's a good thing the author did the interviews prior to development. It's a great way to make sure you do the job right and sadly, not a lot of papers (that present systems) do that.
Reading #26: Picturephone: A Game for Sketch Data Capture (Johnson)
Comment Location:
https://www.blogger.com/comment.g?blogID=19209095&postID=2268287811024365988&isPopup=true
Summary:
Picturephone was introduce in reading #24, so if any background information on Picturephone is necessary, please refer to that paper. The game works in 3 basic steps:
1) party 1 describes picture in text
2) party 2 creates sketch based on text
3) party 3 judges similarity between picture and text description
The paper did not contain a results section, so this leads to doubt about Picturephone's usability testing. The author does state users will only play Picturephone if it is engaging. The author mentioned tools and features used to attract and hold the user's attention, but was careful to state such tools and features should not destroy the original purpose of Picturephone.
Discussion:
I was a little surprised to learn this mini-game had its own paper. I had assumed the author included it in reading #24 and dropped it afterward. The paper does bring up the interesting point that people interpret the same description differently. I once did a similar exercise in an English class in middle school. We all drew a picture based on a textual description and we found both our descriptions and sketches lacking. Give 2 users the same description and you will get 2 different sketches, guaranteed. Coping with this human idiosyncrasy will become a very pertinent topic in future sketch recognition research. I also noticed chunks of text in this paper were identical to chunks of text in reading #24.
https://www.blogger.com/comment.g?blogID=19209095&postID=2268287811024365988&isPopup=true
Summary:
Picturephone was introduce in reading #24, so if any background information on Picturephone is necessary, please refer to that paper. The game works in 3 basic steps:
1) party 1 describes picture in text
2) party 2 creates sketch based on text
3) party 3 judges similarity between picture and text description
The paper did not contain a results section, so this leads to doubt about Picturephone's usability testing. The author does state users will only play Picturephone if it is engaging. The author mentioned tools and features used to attract and hold the user's attention, but was careful to state such tools and features should not destroy the original purpose of Picturephone.
Discussion:
I was a little surprised to learn this mini-game had its own paper. I had assumed the author included it in reading #24 and dropped it afterward. The paper does bring up the interesting point that people interpret the same description differently. I once did a similar exercise in an English class in middle school. We all drew a picture based on a textual description and we found both our descriptions and sketches lacking. Give 2 users the same description and you will get 2 different sketches, guaranteed. Coping with this human idiosyncrasy will become a very pertinent topic in future sketch recognition research. I also noticed chunks of text in this paper were identical to chunks of text in reading #24.
Reading #25: A Descriptor for Large Scale Image Retrieval Based on Sketched Feature Lines (Eitz)
Comment Location:
https://www.blogger.com/comment.g?blogID=19209095&postID=3221243972096915542&isPopup=true
Summary:
This is another attempt to generalize sketch recognition. The previous paper focused on incorporating variances between pictures of the same description, and this paper focuses on scale. The author focuses on searching for and retrieving images from a database of over a million images. The uniqueness of the system stems from the fact that it is an image-based search system. The user sketches an image and that is used as the query in the database.
An edge histogram and tensor descriptor are used to extract the necessary data for the search query. Explaining the definitions and utilization of an edge histogram and tensor descriptor would be too lengthy for this summary, so it is left to the reader to investigate further.
Discussion:
The author achieved promising results. What I would like to see is the computer playing pictionary with a good deal of accuracy. The user draws a sketch and the computer's queries get more specific and have a smaller list of results. All in all, I personally enjoy the idea of an image-based search system.
https://www.blogger.com/comment.g?blogID=19209095&postID=3221243972096915542&isPopup=true
Summary:
This is another attempt to generalize sketch recognition. The previous paper focused on incorporating variances between pictures of the same description, and this paper focuses on scale. The author focuses on searching for and retrieving images from a database of over a million images. The uniqueness of the system stems from the fact that it is an image-based search system. The user sketches an image and that is used as the query in the database.
An edge histogram and tensor descriptor are used to extract the necessary data for the search query. Explaining the definitions and utilization of an edge histogram and tensor descriptor would be too lengthy for this summary, so it is left to the reader to investigate further.
Discussion:
The author achieved promising results. What I would like to see is the computer playing pictionary with a good deal of accuracy. The user draws a sketch and the computer's queries get more specific and have a smaller list of results. All in all, I personally enjoy the idea of an image-based search system.
Reading #24: Games for Sketch Data Collection (Johnson)
Comment Location:
http://ayden-kim.blogspot.com/2010/12/reading-24-games-for-sketch-data.html
Summary:
The author attempts to incorporate the fact that there are multiple ways to draw the same "picture". A person can draw the sun or the moon in a variety of different ways. People will draw different based on a text description. The author introduced 2 games to collect sketches based on certain information (such as a text description) to enable future researchers obtain sketch data. The 2 games are Picturephone and Stellasketch. Picturephone gives the sketchers a description and allows them to draw it. The judgment of the sketch's similarity to the original text description is rated by a 3rd party of humans. Stellasketch is a computer version of Pictionary.
Discussion:
The author brings up some good points. There are many ways of drawing many shapes; a stick figure can be drawn in 720 different ways, and that's a relatively simple sketch. The author tried to make these games "engaging", meaning "fun". I don't see that happening. What would you rather do: play a mentally-stimulating game of Stellasketch or pick up Halo and kill people online with explosives? The answer is a no-brainer, literally.
http://ayden-kim.blogspot.com/2010/12/reading-24-games-for-sketch-data.html
Summary:
The author attempts to incorporate the fact that there are multiple ways to draw the same "picture". A person can draw the sun or the moon in a variety of different ways. People will draw different based on a text description. The author introduced 2 games to collect sketches based on certain information (such as a text description) to enable future researchers obtain sketch data. The 2 games are Picturephone and Stellasketch. Picturephone gives the sketchers a description and allows them to draw it. The judgment of the sketch's similarity to the original text description is rated by a 3rd party of humans. Stellasketch is a computer version of Pictionary.
Discussion:
The author brings up some good points. There are many ways of drawing many shapes; a stick figure can be drawn in 720 different ways, and that's a relatively simple sketch. The author tried to make these games "engaging", meaning "fun". I don't see that happening. What would you rather do: play a mentally-stimulating game of Stellasketch or pick up Halo and kill people online with explosives? The answer is a no-brainer, literally.
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