We have developed a small and low-cost device that realizes both recognizing objects and measuring their distances in all directions: a monocular omnidirectional stereo camera (MOSC). The distortion of the lens and hyperbolic mirror of the MOSC is calibrated parametrically, but there is still distortion that cannot be modeled. In this study, we use a known distance object to correct the disparity itself rather than the image distortion, and achieved 360° horizontal field of view measurement accuracy. This makes it possible to measure and recognize the entire surrounding area at low cost and high accuracy using the MOSC.

Abstract The fastest known classical algorithm deciding the k-colorability of n-vertex graph requires running time $$\varOmega (2^n)$$ Ω ( 2 n ) for $$k\ge 5$$ k ≥ 5 . In this work, we present an exponential-space quantum algorithm computing the chromatic number with running time $$O(1.9140^n)$$ O ( 1 . 9140 n ) using quantum random access memory (QRAM). Our approach is based on Ambainis et al’s quantum dynamic programming with applications of Grover’s search to branching algorithms. We also present a polynomial-space quantum algorithm not using QRAM for the graph 20-coloring problem with running time $$O(1.9575^n)$$ O ( 1 . 9575 n ) . For the polynomial-space quantum algorithm, we essentially develop $$(4-\epsilon )^n$$ ( 4 - ϵ ) n -time classical algorithms that can be improved quadratically by Grover’s search.

This paper proposes a method for retrieving images containing a specific target person from a given image collection of group photos. This can be realized by query-by-example methods which compare the facial visual features of the target person in the given query image and of each person in the images in the image collection. However, since images are often taken under various conditions, facial appearance of the same person can vary. Since socially related people such as family and friends are often taken photos together, the people co-occurrence relations in the same images can also be a useful clue for image retrieval. Focusing on such people co-occurrence relations, we propose Bag of People (BoP) features which represent both the facial appearances of persons and their co-occurrence relations in the same images. By using the BoP features, a classifier for classifying images into two classes, images containing the target person and other images, can be trained from a small number of images labeled by user's relevance feedback. Furthermore, since the labeled images obtained by relevance feedback are much fewer than unlabeled images in the image collection, an active learning method is used to select useful images to train the classifier. When retrieving images of 24 persons in total from 550 images, after five feedback iterations, the mean average precision of 0.94 was obtained by considering the people co-occurrence relations, as against 0.69 when considering only the target person.

This paper proposes an image retrieval method which retrieves images of a specific person from group photos. Many query-by-example methods have focused only on the visual features of the queried person. However, since socially related people such as family and friends are often taken photos together, their co-occurrence relations can be useful information. Thus, we propose an image retrieval method which uses the visual features of not only the queried person but also those who co-occur with the queried person in the same images. Relevance feedback is used to learn who co-occur with the queried person, their faces, and how strong their co-occurrence relations are. When retrieving the images of 19 persons in total from 158 images, after five feedback iterations, the recall rate of 50% was obtained by considering the people co-occurrence relations, as against 33% when considering only the queried person. With human errors in giving relevance feedback, the recall rate still improved to 40%.

A Time-to-Digital-Converter (TDC) is to measure the interval time between two signals, and its time resolution of several pico seconds is achieved when it is implemented with advanced CMOS process [1–5]. Its applications are gradually expanding such as a phase comparator of all-digital-PLL, a sensor interface circuit, modulation circuit and demodulation circuit as well as a TDC-based ADC [1–6]. The TDC will play more important role in nano-CMOS era because it is well-matched to implement with fine digital CMOS process; it consists of mostly digital circuits, and as the switching speed increases, its performance is improved.

In recent years, domino logic has received much attention. But in the case of standard domino logic, only non-inverting gates are allowed. Then, clock-delayed (CD) domino logic, that realizes any logic gate, has been proposed. Moreover, the domino logic has another drawback in that it is very sensitive to noise induced by crosstalk. Therefore, we focus our attention on crosstalk faults in CD domino circuits. In order to realize an efficient fault simulation, in this paper we propose a new method of target fault reduction, considering conflicts of signal values in the circuit and dominance of faults. In addition, we introduce a faster fault simulation method, which uses only logic values without handling details of the timing events of circuits.

With the movement into deep submicron (DSM) technology and GHz clock frequencies, signal integrity problems have become important. Signal integrity problems are induced by circuit noise such as crosstalk, power supply noise. substrate noise. In this paper, we consider crosstalk in such noise and propose a new built-in self-test method for faults induced by crosstalk, called crosstalk faults.

This paper presents a general and computationally inexpensive algorithmic scheme that falls in a region detection category. In the scheme, a minimal spanning tree is used as a path of a sequential region grower. The algorithm traverses the spatially adjacent graph while maintaining the structural organization of an image. The graph-theoretical evaluation of heuristics is described and examples of implementation are given.