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Sparse representation-based methods have been successfully applied to visual tracking. However, complex and inefficient optimization limits their deployment in practical tracking scenarios. In this paper, we propose a temporal consistency dictionary learning tracking algorithm to enable efficient dictionary learning and tracking executive. First, we present an objective function which introduces the fixed dictionary and variance dictionary to reconstruct the object’s appearance. In particular, the proposed method takes the temporal consistency into account by adding a regularization term into the objective function to constrain the difference of object appearance at adjacent frames. Then the optimization problem is solved in an iteration way. Moreover, the proposed method can encode the object’s local structural information, and the local patches from the same candidate altogether for a global appearance representation. Second, we develop an effective observation likelihood function based on the proposed model. It takes the influence of patches with large reconstruction errors into consideration, thereby, alleviating the drifting of the object. Finally, we present an appearance updating strategy to adapt to the object’s appearance variations by the online dictionary learning. Experimental evaluations on the TB50 and TB100 datasets show that the proposed tracking method outperforms sparse representation related visual tracking as well as other state-of-the-art tracking methods. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the guest editor discuss changes within the publication of the journal including its new members of the editorial board.

People whom the author would like to thank for their assistance in the creation of "International Journal of Computer Vision" are mentioned.

The literary anthology is one of the key categories in ancient Chinese literary theory and criticism. Theoretically, anthology criticism focuses on three main areas: the preface and postscript, the annotation of the anthology, and the works selected for inclusion in the anthology. Anthology criticism is unique in its methodological synergy, including the direct and indirect communication of literary judgments and the amalgamation of critical theory and practice. This paper argues that the anthology as a form of literary criticism possesses great theoretical value; it sheds light on the development of literary concepts and forms, as well as suggesting the nature of literary transmission. Therefore, the literary anthology plays a key role in the canonization of Chinese literature. [ABSTRACT FROM AUTHOR]

In our previous work, we reported a system that monitors an intersection using a network of horizontal laser scanners. This paper focuses on an algorithm for moving-object detection and tracking, given a sequence of distributed laser scan data of an intersection. The goal is to detect each moving object that enters the intersection; estimate state parameters such as size; and track its location, speed, and direction while it passes through the intersection. This work is unique, to the best of the authors' knowledge, in that the data is novel, which provides new possibilities but with great challenges; the algorithm is the first proposal that uses such data in detecting and tracking all moving objects that pass through a large crowded intersection with focus on achieving robustness to partial observations, some of which result from occlusions, and on performing correct data associations in crowded situations. Promising results are demonstrated using experimental data from real intersections, whereby, for 1063 objects moving through an intersection over 20 min, 988 are perfectly tracked from entrance to exit with an excellent tracking ratio of 92.9%. System advantages, limitations, and future work are discussed. [ABSTRACT FROM PUBLISHER]

People who the author would like to thank for their assistance in the creation of the journal "International Journal of Computer Vision" are mentioned.

This issue of JAISE is composed of four papers. However, current methods of defining zones heavily depend on the robot's on-board sensing capabilities and often require a direct line of sight between the human user and the robot. The paper B "Representation learning for minority and subtle activities in a smart home environment" b by Sanabria et al. proposes a hierarchical activity classifier based on a two-phase learning scheme. [Extracted from the article]

An introduction is presented in which the editor discusses various reports within the issue on topics including the creation of playful persuasion in designing public spaces, the role of ambient assisted living (AAL) in the achievement of well-being among older people, and a methodology for concrptualizing context for intelligent system.

An introduction is presented in which the editor discusses various reports within the issue on topics including interactive energy management system, estimation of human walking speed and hydraulic bed sensor capturing the superposition of respiration signals and heart rate.

Reviewers whom the "Journal of Ambient Intelligence and Smart Environments" (JAISE) would like to thank for their assistance in the creation of the journal issues from November 2013 to November 2014 are mentioned.