A new approach for multi-target tracking in an occlusion environment is presented. In pedestrian tracking using a video camera, pedestrains must be tracked accurately and continuously in the images. However, in a crowded environment, the conventional tracking algorithm has a problem in that tracks do not continue when pedestrians are hidden behind the foreground object. In this study, we propose a robust tracking method for occlusion that introduces a degeneration hypothesis that relaxes the track hypothesis which has one measurement to one track constraint. The proposed method relaxes the hypothesis that one measurement and multiple trajectories are associated based on the endpoints of the bounding box when the predicted trajectory is approaching, therefore the continuation of the tracking is improved using the measurement in the foreground. A numerical evaluation using MOT (Multiple Object Tracking) image data sets is performed to demonstrate the effectiveness of the proposed algorithm.

Instance features based deep learning methods prompt the performances of high speed object tracking systems by directly comparing target with its template during training and tracking. However, from the perspective of human vision system, prior knowledge of target also plays key role during the process of tracking. To integrate both semantic knowledge and instance features, we propose a convolutional network based object tracking framework to simultaneously output bounding boxes based on different prior knowledge as well as confidences of corresponding Assumptions. Experimental results show that our proposed approach retains both higher accuracy and efficiency than other leading methods on tracking tasks covering most daily objects.

In this paper, the Voronoi region of the transmitted codeword is employed to improve the sphere bound on the maximum-likelihood decoding (MLD) performance of binary linear block codes over additive white Gaussian noise (AWGN) channels. We obtain the improved sphere bounds both on the frame-error probability and the bit-error probability. With the framework of the sphere bound proposed by Kasami et al., we derive the conditional decoding error probability on the spheres by defining a subset of the Voronoi region of the transmitted codeword, since the Voronoi regions of a binary linear block code govern the decoding error probability analysis over AWGN channels. The proposed bound improves the sphere bound by Kasami et al. and the sphere bound by Herzberg and Poltyrev. The computational complexity of the proposed bound is similar to that of the sphere bound by Kasami et al.

In this paper, we propose an RFID distance bounding protocol that uses m-ary challenges. Recently, Kim and Avoine proposed two distance bounding protocols with mixed challenges that are pre-determined or random. We generalize the first scheme of Kim and Avoine's random scheme as a distance bounding protocol with m-ary challenges. The generalized formula for success probabilities for mafia fraud and distance fraud attacks is derived. Our scheme using m-ary challenges reduces the mafia fraud success probability from (3/4)n for m=2 to (7/16)n for m=4 and the distance fraud success probability from $(1-rac 1 4 cdot P_r)^n$ for m=2 to $(1 - rac {189}{256} cdot P_r)^n$ for m=4, where Pr is the probability that a challenge is random.

This paper proposes an algorithm for exemplar-based image inpainting, which produces the same result as that of Criminisi's original scheme but at the cost of much smaller computation cost. The idea is to compute mean and standard deviation of every patch in the image, and use the values to decide whether to carry out pixel by pixel comparison or not when searching for the best matching patch. Due to the missing pixels in the target patch, the same pixels in the candidate patch should be omitted when computing the distance between patches. Thus, we first compute the range of mean and standard deviation of a candidate patch with missing pixels, using the average and standard deviation of the entire patch. Then we use the range to determine if the pixel comparison should be conducted. Measurements with well-known images in the inpainting literature show that the algorithm can save significant amount of computation cost, without risking degradation of image quality.

This paper proposes a novel method for determining a three-dimensional (3D) bounding box to estimate pose (position and orientation) and size of a 3D object corresponding to a segmented object region in an image acquired by a single calibrated camera. The method is designed to work upon an object on the ground and to determine a bounding box aligned to the direction of the object, thereby reducing the number of degrees of freedom in localizing the bounding box to 5 from 9. Observations associated with the structural properties of back-projected object regions on the ground are suggested, which are useful for determining the object points expected to be on the ground. A suitable base is then estimated from the expected on-ground object points by applying to them an assumption of bilateral symmetry. A bounding box with this base is finally constructed by determining its height, such that back-projection of the constructed box onto the ground minimally encloses back-projection of the given object region. Through experiments with some 3D-modelled objects and real objects, we found that a bounding box aligned to the dominant direction estimated from edges with common direction looks natural, and the accuracy of the pose and size is enough for localizing actual on-ground objects in an industrial working space. The proposed method is expected to be used effectively in the fields of smart surveillance and autonomous navigation.

Distance bounding protocols permit a verifier to compute the distance to a prover by measuring the execution time of n rounds of challenge-response authentication. Many protocols have been proposed to reduce the false acceptance rate of the challenge-response procedure. Until now, it has been widely believed that the lowest bound of the false acceptance rate is (1/2)n when n is the number of rounds and the prover can send only one response bit for each round. In this paper, we propose a new distance bounding protocol whose false acceptance rate is (1/3)n against the distance fraud attacks and the mafia fraud attacks. To reduce the false acceptance rate, we use two challenge bits for each iteration and introduce a way of expressing three cases with the use of only one response bit, the same bit length as existing protocols. Our protocol is the first distance bounding protocol whose false acceptance rate is lower than the currently believed minimal bound without increasing the number of response bits for each round.

This letter presents a scheme to improve the running time of exemplar-based image inpainting, first proposed by Criminisi et al. In the exemplar-based image inpainting, a patch that contains unknown pixels is compared to all the patches in the known region in order to find the best match. This is very time-consuming and hinders the practicality of Criminisi's method to be used in real time. We show that a simple bounding algorithm can significantly reduce number of distance calculations, and thus the running time. Performance of the bounding algorithm is affected by the order of patches that are compared, as well as the order of pixels in a patch. We present pixel and patch ordering schemes that improve the performance of bounding algorithms. Experiments with well-known images used in inpainting literature show that the proposed reordering scheme can reduce running time of the bounding algorithm up to 50%.

A distance bounding protocol provides an upper bound on the distance between communicating parties by measuring the round-trip time between challenges and responses. It is an effective countermeasure against mafia fraud attacks (a.k.a. relay attacks). The adversary success probability of previous distance bounding protocols without a final confirmation message such as digital signature or message authentication code is at least . We propose a unilateral distance bounding protocol without a final confirmation message, which reduces the adversary success probability to .

Traditional authentication protocols are based on cryptographic techniques to achieve identity verification. Distance bounding protocols are an enhanced type of authentication protocol built upon both signal traversal time measurement and cryptographic techniques to accomplish distance verification as well as identity verification. A distance bounding protocol is usually designed to defend against the relay attack and the distance fraud attack. As there are applications to which the distance fraud attack is not a serious threat, we propose a streamlined distance bounding protocol that focuses on the relay attack. The proposed protocol is more efficient than previous protocols and has a low false acceptance rate under the relay attack.

Ray tracing is one of the most popular techniques for generating photo-realistic images. Extensive research and development work has made interactive static scene rendering realistic. This paper deals with interactive dynamic scene rendering in which not only the eye point but also the objects in the scene change their 3D locations every frame. In order to realize interactive dynamic scene rendering, RTRPS (Ray Tracing based on Ray Plane and Bounding Sphere), which utilizes the coherency in rays, objects, and grouped-rays, is introduced. RTRPS uses bounding spheres as the spatial data structure which utilizes the coherency in objects. By using bounding spheres, RTRPS can ignore the rotation of moving objects within a sphere, and shorten the update time between frames. RTRPS utilizes the coherency in rays by merging rays into a ray-plane, assuming that the secondary rays and shadow rays are shot through an aligned grid. Since a pair of ray-planes shares an original ray, the intersection for the ray can be completed using the coherency in the ray-planes. Because of the three kinds of coherency, RTRPS can significantly reduce the number of intersection tests for ray tracing. Further acceleration techniques for ray-plane-sphere and ray-triangle intersection are also presented. A parallel projection technique converts a 3D vector inner product operation into a 2D operation and reduces the number of floating point operations. Techniques based on frustum culling and binary-tree structured ray-planes optimize the order of intersection tests between ray-planes and a sphere, resulting in 50% to 90% reduction of intersection tests. Two ray-triangle intersection techniques are also introduced, which are effective when a large number of rays are packed into a ray-plane. Our performance evaluations indicate that RTRPS gives 13 to 392 times speed up in comparison with a ray tracing algorithm without organized rays and spheres. We found out that RTRPS also provides competitive performance even if only primary rays are used.

The heterogeneous autonomous decentralized system technology offers a way to integrate different types of context-related autonomous decentralized (sub) systems into a coherent system. The aim of this research is to model and evaluate the communication capacity among the subsystems connected by communication gateways of a heterogeneous autonomous decentralized system. Failures of subsystems and communication gateways in the system are taken into account. We use graphs to represent the topologies of heterogeneous autonomous decentralized systems and use the residual connectedness reliability (RCR) to characterize the communication capacity among its subsystems connected by its gateways. This model enables us to share research results obtained in residual connectedness reliability study in graph theory. Not to our surprise, we learnt soon that computing RCR of general graphs is NP-hard. But to our surprise, there exist no efficient approximation algorithms that can give a good estimation of RCR for an arbitrary graph when both vertices and edges may fail. We proposed in this paper a simulation scheme that gave us good results for small to large graphs but failed for very large graphs. Then we applied a theoretical bounding approach. We obtained expressions for upper and lower bounds of RCR for arbitrary graphs. Both upper and lower bound expressions can be computed in polynomial time. We applied these expressions to several typical graphs and showed that the differences between the upper and lower bounds tend to zero as the sizes of graphs tend to infinite. The contributions of this research are twofold, we find an efficient way to model and evaluate the communication capacity of heterogeneous autonomous decentralized systems; we contribute an efficient algorithm to estimate RCR in general graph theory.