Model-based viewpoint invariant human activity recognition from uncalibrated monocular video sequence

There is growing interest in human activity recognition systems, motivated by their numerous promising applications in many domains. Despite much progress, most researchers have narrowed the problem towards fixed camera viewpoint owing to inherent difficulty to train their systems across all possible viewpoints. Fixed viewpoint systems are impractical in real scenarios. Therefore, we attempt to relax the fixed viewpoint assumption and present a novel and simple framework to recognize and classify human activities from uncalibrated monocular video source from any viewpoint. The proposed framework comprises two stages: 3D human pose estimation and human activity recognition. In the pose estimation stage, we estimate 3D human pose by a simple search-based and tracking-based technique. In the activity recognition stage, we use Nearest Neighbor, with Dynamic Time Warping as a distance measure, to classify multivariate time series which emanate from streams of pose vectors from multiple video frames. We have performed some experiments to evaluate the accuracy of the two stages separately. The encouraging experimental results demonstrate the effectiveness of our framework

Mechanism design for dynamic double auctions

Cette thèse a pour objet de concevoir des mécanismes d'allocation dans le contexte des enchères doubles dynamiques (achats groupés, bourses électroniques). Le principal défi inhérent à la conception de tels mécanismes est d'aboutir à un résultat socialement optimal alors que la dynamique induit une incertitude sur les arrivées et départs des participants de l'enchère ainsi que sur les valuations qui peuvent être fluctuantes. Dans cette thèse, nous proposons des mécanismes qui sont efficaces, incitatifs et garantissant l'équilibre du budget. La définition de ces mécanismes s'appuient sur les algorithmes d'appareillage pour des graphes bipartis (technique d'augmentation et réduction) ainsi que sur une méthode générale prenant en compte le comportement des participants.This thesis addresses the problem of designing mechanisms that lead to socially desirable outcomes in dynamic double auction markets such as stock exchanges and group buying. The main challenge of the design is dealing with the uncertainty posed by the participants who are dynamically arriving and departing and their valuations vary over time. The thesis demonstrates the difficulties in designing mechanisms with desirable properties such as truthfulness, efficiency and budget balance. It also provides dedicated mechanisms satisfying those properties by using augmentation, reduction and behaviour-based approaches

A Free Exchange e-Marketplace for Digital Services

The digital era is witnessing a remarkable evolution of digital services. While the prospects are countless, the e-marketplaces of digital services are encountering inherent game-theoretic and computational challenges that restrict the rational choices of bidders. Our work examines the limited bidding scope and the inefficiencies of present exchange e-marketplaces. To meet challenges, a free exchange e-marketplace is proposed that follows the free market economy. The free exchange model includes a new bidding language and a double auction mechanism. The rule-based bidding language enables the flexible expression of preferences and strategic conduct. The bidding message holds the attribute-valuations and bidding rules of the selected services. The free exchange deliberates on attributes and logical bidding rules for automatic deduction and formation of elicited services and bids that result in a more rapid self-managed multiple exchange trades. The double auction uses forward and reverse generalized second price auctions for the symmetric matching of multiple digital services of identical attributes and different quality levels. The proposed double auction uses tractable heuristics that secure exchange profitability, improve truthful bidding and deliver stable social efficiency. While the strongest properties of symmetric exchanges are unfeasible game-theoretically, the free exchange converges rapidly to the social efficiency, Nash truthful stability, and weak budget balance by multiple quality-levels cross-matching, constant learning and informs at repetitive thick trades. The empirical findings validate the soundness and viability of the free exchange

Maximal matching for double auction

We study the problem of mechanism design for a double auction market where multiple buyers and sellers buy and sell a commodity. We design and implement a matching algorithm that maximizes market liquidity, including the number of transactions and buy/sell-volume. We prove that, given the number of matches, the algorithm also maximizes auctioneer's profit. Based on the CAT Tournament (Trading Agent Competition Market Design) platform, we show with experiments that the new matching method not only increases market liquidity but also significantly improves market share and auctioneer's profit in the long term, compared with equilibrium matching, the most commonly used matching method