Tadayoshi Shioyama

Automated Two-machine Flowshop Scheduling: A Solvable Case

Abstract This paper considers new flowshop scheduling problems related to automated manufacturing systems in which n jobs are processed on two machines Ma and Mb in this order. The job transportation between two machines is done by a single automated guided vehicle (AGV), and is crucial because no machine has buffer storage for work-in-process (WIP) and hence a machine cannot release a finished job until the empty AGV becomes available at that machine, while the AGV cannot transfer an unfinished job to a machine until the machine is empty. O(n 3) algorithms are given in this paper to find optimal sequences of n jobs that minimize their maximum completion time (i.e., makespan). Some numerical results are also given to evaluate the effect of computing optimal sequences.

Glasses frame detection with 3D Hough transform

This paper describes a method to detect glasses frames for robust facial image processing. This method makes use of the 3D features obtained by a trinocular stereo vision system. The glasses frame detection is based on the fact that the rims of a pair of glasses lie on the same plane in 3D space. We use a 3D Hough transform to obtain a plane in which 3D features are concentrated. Then, based on the obtained 3D plane and with some geometry constraints, we can detect a group of 3D features belonging to the frame of the glasses. Using this approach, we can separate the 3D features of the glasses frame from those of facial features. This approach does not require any prior knowledge about face pose, eye positions, or the shape of the glasses.

Bipolarity and Projective Invariant-Based Zebra-Crossing Detection for the Visually Impaired

A safe road-crossing system is an extreme necessity to improve the mobility of the visually impaired. It is important for a blind person to know whether a frontal area is a crossing or not. A crossing is characterized by zebra pattern i.e. by constant width periodic white stripes on a usual black road surface, which can be treated as a bipolar pattern. In this paper, a fast and stable algorithm for detecting the location of a pedestrian crossing using an image captured by a single camera is presented. This is achieved through bipolarity-based segmentation and projective invariant-based recognition. The algorithm includes three steps. First, we segment the image on the basis of bipolarity and pick the crossing candidates on the basis of area. Second, feature points are extracted on the candidate area based on Fisher criterion. Third, we use projective invariants to recognize the crossing. The experiments on a large number of street scenes with and without crossing demonstrate the effectiveness of the proposed algorithm.

Optimal Gabor filters for high speed face identification

This paper describes a fast face identification method with Gabor filters. Two efforts are made to achieve the acceptable processing speed: 1) we design the optimal Gabor filters with the arrangement theory that uses a few directions and layers; and 2) the transformation with Gabor filters (called Gabor transformation) is only done over the regions around the facial feature points, not the whole input image. The facial feature points extraction is performed by detecting the facial organ regions with color information and edge information, followed by, the corner detection in each detected facial organ region with the SUSAN operator.

Measurement of the length of pedestrian crossings and detection of traffic lights from image data

This paper proposes a method for measurement of the length of a pedestrian crossing and for the detection of traffic lights from image data observed with a single camera. The length of a crossing is measured from image data of white lines painted on the road at a crossing by using projective geometry. Furthermore, the state of the traffic lights, green (go signal) or red (stop signal), is detected by extracting candidates for the traffic light region with colour similarity and selecting a true traffic light from them using affine moment invariants. From the experimental results, the length of a crossing is measured with an accuracy such that the maximum relative error of measured length is less than 5% and the rms error is 0.38 m. A traffic light is efficiently detected by selecting a true traffic light region with an affine moment invariant.

Spotting recognition of head gestures from color image series

Presents an approach for spotting recognition of human head gestures from color image series. First, we use an algorithm based on a perceptually uniform color system to detect skin color region and hair color region of the face from input images. Then, the 3D pose of the head relative to the camera is estimated by calculating the primary moment and secondary moment of the skin color region and the hair color region. The standard patterns of each gesture were represented by the sequence of rotation angles in X, Y, Z axis, and the head area. Moreover the human head gestures were recognized by using the continuous dynamic programming algorithm to compare input image series with the standard patterns. Extensive experiments show the effectiveness of this approach in the human head gestures recognition from live video sequences with different people even wearing glasses, with different head size, and with unknown complex background.

Optimal control of a queuing network system with two types of customers

Abstract We deal with an optimal control problem in a queuing network system. The system consists of the first stage with a server and the second stage with two servers each having its finite queue. Two types of customers are first served at the first stage server and subsequently proceed to the queue at the server corresponding to their types in the second stage. When the first stage server completes a service, he determines the type of customer to be next served. The optimal control problem is to select the type of customer to be next served in order to minimize the expected cost per hour. The problem is formulated as an undiscounted semi-Markov decision process. The monotonicity of the optimal policy is shown.

Detection of pedestrian crossing and measurement of crossing length - an image-based navigational aid for blind people

Pedestrian crossings are dangerous places for a visually impaired person to cross safely. This paper describes a simple method for the detection of the location of a pedestrian crossing as well as measurement of its length to enhance the safety and mobility of blind people while crossing a road. A crossing is characterized by zebra pattern i.e. by evenly spaced white stripes on a usual black road surface. Detection of the crossing location as well as measurement of its length is done using this criterion from the image captured by a single camera. The method at first checks for the existence of a crossing; if there exists a crossing then it goes to measure the crossing length. Experimental results on a large number of street scenes with and without crossings demonstrate the effectiveness of the proposed technique.

Detection of pedestrian crossing using bipolarity feature-an image-based technique

This paper presents a novel approach for detecting pedestrian crossings to enhance the safety and mobility of blind people while crossing a road. It is extremely important for a blind person to know whether a frontal area is a crossing or not. In a crossing, the usual black road surface is painted with constant-width periodic white bands. An image-based technique has been developed to detect the bipolar patterns of pedestrian crossings. The presence of pedestrian crossings are inferred by careful analysis of crossing width, crossing direction, number of crossing bands, as well as bandwidth trend. Experimental evaluation of the proposed approach was conducted using 100 real images with and without crossings. It was found that the proposed technique performed with 95% accuracy and with no false positive.

Image analysis of crosswalk

This paper proposes a method for image analysis of a crosswalk and a traffic light. The method provides information not only about the length of a crosswalk, but also about the colour of the traffic light. The length of a crosswalk is estimated by projective geometry using white lines painted on the road at a crosswalk. Furthermore, the state of the traffic light, that is, the colour of green (walk signal) or red (stop signal), is detected by searching the green (or red) traffic light using affine moment invariants. In order to evaluate the performance, experimental results estimating the length and detecting the traffic light are presented.