Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-Identification

Online multi-object tracking is a fundamental problem in time-critical video analysis applications. A major challenge in the popular tracking-by-detection framework is how to associate unreliable detection results with existing tracks. In this paper, we propose to handle unreliable detection by collecting candidates from outputs of both detection and tracking. The intuition behind generating redundant candidates is that detection and tracks can complement each other in different scenarios. Detection results of high confidence prevent tracking drifts in the long term, and predictions of tracks can handle noisy detection caused by occlusion. In order to apply optimal selection from a considerable amount of candidates in real-time, we present a novel scoring function based on a fully convolutional neural network, that shares most computations on the entire image. Moreover, we adopt a deeply learned appearance representation, which is trained on large-scale person re-identification datasets, to improve the identification ability of our tracker. Extensive experiments show that our tracker achieves real-time and state-of-the-art performance on a widely used people tracking benchmark.Comment: ICME 201

High pointwise emergence and Katok's conjecture for systems with non-uniform structure

Recently, Kiriki, Nakano and Soma introduced a concept called pointwise emergence as a new quantitative perspective into the study of non-existence of averages for dynamical systems. In the present paper, we consider the set of points with high pointwise emergence for systems with non-uniform structure and prove that this set carries full topological pressure. For the proof of this result, we show that such systems have ergodic measures of arbitrary intermediate pressures

Unbending strategies shepherd cooperation and suppress extortion in spatial populations

Evolutionary game dynamics on networks typically consider the competition among simple strategies such as cooperation and defection in the Prisoner's Dilemma and summarize the effect of population structure as network reciprocity. However, it remains largely unknown regarding the evolutionary dynamics involving multiple powerful strategies typically considered in repeated games, such as the zero-determinant (ZD) strategies that are able to enforce a linear payoff relationship between them and their co-players. Here, we consider the evolutionary dynamics of always cooperate (AllC), extortionate ZD (extortioners), and unbending players in lattice populations based on the commonly used death-birth updating. Out of the class of unbending strategies, we consider a particular candidate, PSO Gambler, a machine-learning-optimized memory-one strategy, which can foster reciprocal cooperation and fairness among extortionate players. We derive analytical results under weak selection and rare mutations, including pairwise fixation probabilities and long-term frequencies of strategies. In the absence of the third unbending type, extortioners can achieve a half-half split in equilibrium with unconditional cooperators for sufficiently large extortion factors. However, the presence of unbending players fundamentally changes the dynamics and tilts the system to favor unbending cooperation. Most surprisingly, extortioners cannot dominate at all regardless of how large their extortion factor is, and the long-term frequency of unbending players is maintained almost as a constant. Our analytical method is applicable to studying the evolutionary dynamics of multiple strategies in structured populations. Our work provides insights into the interplay between network reciprocity and direct reciprocity, revealing the role of unbending strategies in enforcing fairness and suppressing extortion.Comment: 21 pages, 6 figure

Emotion-Driven User Experience on Elderly Women’s Impulse Buying：A Kano Model study

This study examines how emotion-driven user experience (UX) design influences impulse buying among women aged 50-59 in online fashion shopping. Using the Kano model, it categorizes UX elements—visual appeal, social interaction, and personalized recommendations—into basic, performance, and attractive needs. A survey of 265 women reveals that emotionally engaging features significantly drive impulse purchases, though their impact on loyalty is limited. Key findings highlight the importance of visual aesthetics and personalized experiences. This research provides actionable insights for optimizing UX design to enhance engagement and purchasing behavior, with implications for future studies on other demographics and industries

Does institutional ownership increase market quality? Empirical evidence from the financial crisis

This dissertation aims to examine the relationship between institutional ownership and stock market quality. By using stock data from US S&P 500 index constituent, this dissertation empirically studied how the volatility, returns, and liquidity of the stocks are impacted by institutional investors. This dissertation also considered the impact of the 2008 financial crisis and the short sale restrictions enforced during the crisis. According to the OLS regression results, this paper discovered there is a positive association between institutional ownership and stock return and liquidity. There is a negative correlation between institutional ownership and stock return volatility. Besides, this dissertation further study how different is the impact of institutional ownership on financial stocks and non-financial stocks. The positive impact of institutional ownership on the return of financial stocks is weaker than non-financial stocks, and the impact of institutional ownership on volatility and bid-ask spread of financial stocks is positive. In addition, the impact of institutional ownership on volatility and liquidity of financial stocks is weakened by the short sale restrictions. The financial crisis also weakens the impact of institutional ownership on volatility and bids-ask spread of non-financial stocks