Exploring Human Vision Driven Features for Pedestrian Detection

Motivated by the center-surround mechanism in the human visual attention system, we propose to use average contrast maps for the challenge of pedestrian detection in street scenes due to the observation that pedestrians indeed exhibit discriminative contrast texture. Our main contributions are first to design a local, statistical multi-channel descriptorin order to incorporate both color and gradient information. Second, we introduce a multi-direction and multi-scale contrast scheme based on grid-cells in order to integrate expressive local variations. Contributing to the issue of selecting most discriminative features for assessing and classification, we perform extensive comparisons w.r.t. statistical descriptors, contrast measurements, and scale structures. This way, we obtain reasonable results under various configurations. Empirical findings from applying our optimized detector on the INRIA and Caltech pedestrian datasets show that our features yield state-of-the-art performance in pedestrian detection.Comment: Accepted for publication in IEEE Transactions on Circuits and Systems for Video Technology (TCSVT

APTE: An Algorithm for Proving Trace Equivalence

This paper presents APTE, a new tool for automatically proving the security of cryptographic protocols. It focuses on proving trace equivalence between processes, which is crucial for specifying privacy type properties such as anonymity and unlinkability. The tool can handle protocols expressed in a calculus similar to the applied-pi calculus, which allows us to capture most existing protocols that rely on classical cryptographic primitives. In particular, APTE handles private channels and else branches in protocols with bounded number of sessions. Unlike most equivalence verifier tools, APTE is guaranteed to terminate Moreover, APTE is the only tool that extends the usual notion of trace equivalence by considering ``side-channel'' information leaked to the attacker such as the length of messages and the execution times. We illustrate APTE on different case studies which allowed us to automatically (re)-discover attacks on protocols such as the Private Authentication protocol or the protocols of the electronic passports

Support of Collaborative Structural Design Processes through the Integration of Peer-to-Peer and Multiagent Architectures

Structural engineering projects are increasingly organized in networked cooperations due to a permanently enlarged competition pressure and a high degree of complexity while performing the concurrent design activities. Software that intends to support such collaborative structural design processes implicates enormous requirements. In the course of our common research work, we analyzed the pros and cons of the application of both the peer-to-peer (University of Bonn) and multiagent architecture style (University of Bochum) within the field of collaborative structural design. In this paper, we join the benefits of both architecture styles in an integrated conceptual approach. We demonstrate the surplus value of the integrated multiagent–peer-to-peer approach by means of an example scenario in which several structural engineers are co-operatively designing the basic structural elements of an arched bridge, applying heterogeneous CAD systems

Takeovers, Governance and The Cross-Section of Returns

This paper considers the impact of the takeover channel on firm valuation. We use the idea that takeover activity responds to investor expectations of future rate of return and hence to state variable(s) related to the time variation in risk premia. Thus firms with higher exposure to takeovers, due to higher expectations of receiving a takeover premium, have a higher exposure to the state variable that dictates time variation in risk premia. Consequently, the difference in the returns between firms that differ in their takeover vulnerabilities can be used to used to proxy these state variables. To do so, we create a takeover-spread portfolio that buys firms with low cash-adjusted-leverage (cheaper targets) and shorts firms with high cash-adjusted-leverage and show that such a portfolio generates annualized abnormal returns of up to 11.20% between 1980 and 2003. Also, abnormal returns associated with governance-spread portfolios (Gompers, Ishii and Metrick, 2003 and Cremers and Nair, 2004) decrease significantly once the asset pricing model includes this ’cash-adjusted-leverage’ factor. Finally, we propose a new ‘takeover’ factor to proxy for the risk due to changes in these risk-premia related state variables, which is shown to be important in explaining cross-sectional differences in equity returns. The paper shows why investors require a higher rate of return on firms exposed to takeovers and yet value them higher than firms protected from takeovers

The Impact of Shareholder Control on Bondholders

This paper investigates the effect of shareholder control on bondholder wealth. While stronger shareholder control can benefit bondholders by disciplining managers, it also increases the likelihood of events that can hurt bondholders, e.g. hostile takeovers. We hypothesize that shareholder control can have contrasting effects on bond yields depending on the takeover vulnerability of a firm. Using the presence of an institutional blockholder to proxy for shareholder control and firm-level anti-takeover provisions to proxy for takeover vulnerability, we find that shareholder control is associated with lower yields if the firm is protected from takeovers. We also find that shareholder control is associated with higher yields if the firm is exposed to takeovers. The contrasting effects of shareholder control on yields are the strongest for firms that are small and have low leverage. In the presence of shareholder control, the difference in bond yields due to differences in takeover vulnerability can be as high as 93 basis points. Further, the results are insignificant for a sub-sample of firms where the bondholders are protected from takeovers through the poison put covenant. Bond ratings also appear to incorporate a similar effect of shareholder control on bondholders Finally, we find that a bond pricing model that does not account for shareholder control generates an annualized abnormal return of 1% to 1.4% for portfolios that long firms with both strong shareholder control and high takeover vulnerability and short firms without either shareholder control or takeover vulnerability. Combined, these results suggest that the use of different governance mechanisms, such as shareholder monitoring and takeover vulnerability, depends on a firm’s capital structure and that bond-pricing models should account for shareholder control

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification of a shape prior using kernel density estimation is a natural technique. Unfortunately, energy functionals arising from kernel density estimation are of a form that makes them impossible to directly minimize using efficient optimization algorithms such as graph cuts. Our main contribution is to show how one may recast the energy functional into a form that is minimizable iteratively and efficiently using graph cuts.Comment: Revision submitted to JMIV (02/24/13