Somkiat Wangsiripitak

Visual Programming using Flowchart

Nowadays a computer programming become the fundamental knowledge for people studying or working in a computer field, e.g. computer engineering, computer science, information technology, etc. Programmer not only considers the algorithm carefully but also performs the coding according to the syntax of programming language used. Therefore writing a computer program is a difficult task, especially for a beginner. In fact, a novice often uses a flowchart as a tool to help him summarize the idea into all necessary steps of solution, but this flowchart cannot be understood by the computer. It must be converted to the program by using some programming language and then be compiled and run. The visual programming using flowchart proposed in this paper allows the programmer to write the program in the format of flowchart, then compiles and run, without the coding step. There is no necessity to remember the syntax of any programming languages. It takes the benefits of easy-to-understand and easy-to-perform of the flowchart, whereas eliminates the weakness of a conventional programming, e.g. the requirement of remembering the syntax, the error in coding step. Furthermore, a debugging of program by the proposed system is straightforward and easy to discover the error. The proposed system could be used as a tool for teaching the basic concept of structural programming as well. Experimental results show the powerfulness, easiness, and user-friendliness of the proposed system

Feature-based motion detection and tracking on approximate 3D ground plane

The success of movement detection based on the distance moved in a 2D image sequence depends highly on the angle between a cameras optical axis and the normal vector of the ground plane on which the moving object is traveling. When the same 3D displacement occurs at various positions in the scene, the higher the angle is, the greater the distance observed in the image at a position close to camera differs from (strictly speaking, is larger than) those happening at the far end. As a consequence, a detection failure and/or false alarm may occur if no such 3D geometry is utilized. This paper estimates a 3D ground plane, which is then used to measure the approximate 3D displacement of features being detected and tracked. The 3D distances are therefore available and utilized in deciding whether they are of moving objects or just blinking features caused by illumination changes. FAST points are used to enhance a real-time system. Experimental results show superior performance in tracking: a longer trace of continuous tracking, a higher number of detected moving features, earlier detection, better recall rate, no misses, and no false alarms. A SURF descriptor and FLANN matcher were utilized here, however the robustness was not much enhanced when compared to the expense of finding the best match.

Tracking-based human entry/exit detection on various video resolutions (A study on parameter effects)

A real-time tracking-based change detection using FAST features and a background feature model are proposed as a base system for detection of human entrance and exit. A speedy FAST feature extraction and tracking has to trade-off its accuracy, which sometimes causes a failure in human entrance/exit detection. Many video sizes are therefore tested in the system to examine the trade-off effects on the accuracy of feature extraction, tracking, and entry/exit detection. Tracking parameters are also investigated to determine the optimal values for each video resolution, such that stable tracking and detection are achieved. Experimental results show that the higher the video resolution is the more the error is likely to happen. Instability of feature extraction and position which increases in higher resolution is proved to be the main reason of failure. Increasing the number of previous images used in the update of background feature model, proportional to the resolution of video, takes into account the feature uncertainty. As the result, the proposed method is robust to changes in video resolution and runs at 30 fps without a miss of human entrance/exit detection and false alarm.

Vision-Based System for Automatic Detection of Suspicious Objects on ATM

Most skimming devices attached to an automatic teller machine (ATM) are similar in color and shape to the host machine, vision-based detection of such things is therefore difficult. A background subtraction method may be used to detect changes in a normal situation. However, without human detection, its background model is sometimes polluted by the ATM user, and the method cannot detect suspicious objects left in the scene. This paper proposes a real-time system which integrates (i) a simple image subtraction for detection of user arrival and departure, and (ii) an automatic detection of suspicious objects left on the ATM. The background model is updated only when no user is found, and used to detect suspicious objects based on a guided adaptive threshold. To avoid a detection miss, nonlinear enhancement is applied to amplify the intensity differences between foreign objects and host machine. Experimental results show that the proposed system increases correctly detected area by 13.21% compared with the fixed threshold method. It has no detection miss and false alarm either.

In-building navigation system using a camera

A top-view map of building floor is still used nowadays by a visitor for in-building navigation. Its practicality heavily relies on the users skill in matching a current position on the map. When the map is installed at a fixed position, not held in hand, the position of the map itself can be marked in the map, allowing the user to know the current position. Searching for the map itself, however, is still a necessary task. An orientation of the user is another issue of this traditional approach. It can be solved by having one more map point matched with the corresponding physical position on the floor. People with a good sense of direction have no difficulties with this conventional in-building navigation, but neither do the others. This paper uses the PTAM (parallel tracking and mapping - one type of visual simultaneous localization and mapping, SLAM) as a base system in which a camera is the only sensor. Two map points and their corresponding real position are used for registration of the camera pose acquired from PTAM with the top-view map coordinates. The top-view map of current floor is the only thing obtained in advance. Experimental results show that the proposed monocular navigation system can be used to navigate in the building in real-time, which helps the user correctly decide the route to the destination, similar to a GPS system used for the vehicle navigation.