Reading #30

Comments:
Ozgur

Summary:

The paper introduced Tahuti, a geometrical sketch recognition system, which can create UML diagrams. Proposed system uses a multi-layer framework for sketch recognition. The stages of the multi-layer recognition framework are: 1) Preprocessing 2) Selection 3) Recognition 4) Identification.  Through user studies, the authors discovered that Tahuti's interpreted view was deemed to be easier to drawn in and easier to edit in than comparative systems.

Discussion:

This is a new area of application of sketch recognition. UML diagrams contains nearly all the straight lines. This makes the processing much easier. The system allows people to drag and move. This is a great idea of application.

Reading #29

Comment:
Wen zhe

Summary:

This paper provides an system that takes acoustic-based input,  as the name say, scratch. The user proposed to use a modified stethoscope through solid materials, a mic is attached to the surface. It is particularly good to amplifying sound and detecting high frequency noises. The author claim an average accuracy of 89.5%.

Discussion:

In my opinion, the major handicap of this idea is how to eliminate the noise. Compared wit sketch, scratch is much more noisy. And some systems even consider scratch itself as kind of noise. Maybe the stethoscope mic is the key to make this idea work. Well, I am not sure about the stethoscope. Make it plays all the magic in this paper.

Reading #28

Comments:
Ozgur

Summary:

This paper provides an evaluate system about how well people draw the face. From image side, face recognition is applied to model features from the desired human face. From the user side, a sketch recognition is applied to measure how similar it is to the features from human face of image. More over, the system can guide user step by step to draw a more accurate face.

Discussion:

This is a good way of combining computer vision technique with sketch technique. Feature extraction from face image is not very hard, the real hard part is how you can come up with this interesting application.

Reading #27

Comments:
Jianjie

Summary:

This paper proposed an animation tool K-Sketch that can help novice to create animations. This is a pen-based system that requires the user to give timing and spatial information.  This paper has adopted a novel optimization algorithm that makes the whole system simultaneously fast. K-Sketch currently supports all ten desired animation

operations: Translate, Scale, Rotate, Set Timing, Move Relative, Appear, Disappear, Trace, Copy Motion, and Orient to Path.

Discussion:

I have been wondering how sketch can be efficiently used for creating animation, and then here comes this paper. I really want to see how it works, the data from paper can not convince me how it really feels like.

Reading #26

Comments:
Jonathon

Summary:

This paper proposed a sketch-based game for collecting data on how people make and describe sketches. Actually Picture-phone has been talked in Reading 24. This paper has given a detailed description as well as the implementation of the system.

The system has three  mode:

Draw: Text description is given and players are asked to draw according to it.

Describe: Inverse as Draw, sketch is given, and players need to described.

Rate: Player needs to judge how well the drawings matches.

Discussion:

Not much to say about this paper, since it is the same one as in Reading #24. But more detailed. Again, this is really an interesting way of collecting datas.

Reading #25

Comments:
Jinjie

Summary:

This paper proposed a method of retrieving image with combined text information and sketch information. The whole is based on a descriptor, which is constructed by both color image and sketch, where the sketch actually provides the edges of the desired images. An edge histogram descriptor in a cell will be stored for each image. It takes up to 3 seconds to search an image among 1.5 million images.

Discussion:

The major contribution of this paper is the idea of using  sketch information combined with text. We have all experienced using text description to find a picture. It does not work well. This is really a very interesting idea of using sketch.

Reading #24

Comments:
Sampath

Summary:

This paper provides a game system where players interact from drawing. The system collects the raw sketch input and associate it with text information. Two game systems have been described in the paper, Picture-phone and Stella-sketch. While Picture-phone supports people to play at their own rate, a game of Stella-sketch  requires several people to play at the same rate.

Discussion:

In general, This paper has presented Picture-phone and Stella-sketch, two sketching games for collecting data about how people make and describe hand-made drawings. It is very interesting idea, since the game system will of course attract more people to collect data.